Tanzania - Demographic and Health Survey - 2016

Publication date: 2016

Tanzania Demographic and Health Survey and Malaria Indicator Survey 2015-16 Tanzania 2015-16 D em ographic and H ealth S urvey and M alaria Indicator S urvey United Republic of Tanzania Tanzania Demographic and Health Survey and Malaria Indicator Survey 2015-2016 Final Report Ministry of Health, Community Development, Gender, Elderly and Children Dar es Salaam Ministry of Health Zanzibar National Bureau of Statistics Dar es Salaam Office of Chief Government Statistician Zanzibar ICF Rockville, Maryland USA December 2016 The 2015-16 Tanzania Demographic and Health Survey and Malaria Indicator Survey (2015-16 TDHS-MIS) was implemented by the National Bureau of Statistics (NBS) and Office of the Chief Government Statistician (OCGS), Zanzibar, in collaboration with the Ministry of Health, Community Development, Gender, Elderly and Children, Mainland, and the Ministry of Health, Zanzibar. ICF provided technical assistance. The 2015- 16 TDHS-MIS is part of the worldwide DHS Program, which assists countries in the collection of data to monitor and evaluate population, health, and nutrition programs. The survey was funded by the Government of Tanzania, United States Agency for International Development (USAID), Global Affairs Canada, Irish Aid, United Nations Children’s Fund (UNICEF), and United Nations Population Fund (UNFPA). Additional information about the 2015-16 TDHS-MIS may be obtained from the National Bureau of Statistics, Head Office, 18 Kivukoni Road, P.O. Box 796, 11992, Dar es Salaam, Tanzania. Telephone: 255- 22-212-2722/3; Fax: 255-22-213-0852; E-mail: dg@nbs.go.tz; Internet: www.nbs.go.tz. Information about The DHS Program can be obtained from ICF, 530 Gaither Road, Suite 500, Rockville, MD 20850 USA. Telephone: 301-407-6500; Fax: 301-407-6501; E-mail: info@DHSprogram.com; Internet: http://www.DHSprogram.com. Recommended citation: Ministry of Health, Community Development, Gender, Elderly and Children (MoHCDGEC) [Tanzania Mainland], Ministry of Health (MoH) [Zanzibar], National Bureau of Statistics (NBS), Office of the Chief Government Statistician (OCGS), and ICF. 2016. Tanzania Demographic and Health Survey and Malaria Indicator Survey (TDHS-MIS) 2015-16. Dar es Salaam, Tanzania, and Rockville, Maryland, USA: MoHCDGEC, MoH, NBS, OCGS, and ICF. Contents • iii CONTENTS TABLES AND FIGURES . ix FOREWORD . xix ACKNOWLEDGEMENTS . xxi READING AND UNDERSTANDING TABLES FROM THE 2015 TDHS-MIS . xxiii ACRONYMS AND ABBREVIATIONS . xxxiii MAP OF TANZANIA . xxxvi 1 INTRODUCTION AND SURVEY METHODOLOGY . 1 1.1 Geography, History, and the Economy . 1 1.1.1 Geography . 1 1.1.2 History . 1 1.1.3 Economy . 1 1.2 Population . 2 1.3 Population and Health Policies and Programmes . 2 1.3.1 National Population Policy . 2 1.3.2 Vision 2025 . 3 1.3.3 The National Strategy got Growth and Reduction of Poverty (NSGRP) . 3 1.3.4 The 5-Year Development Plan (FYDP I) 2011/12–2015/16 . 3 1.3.5 Big Results Now Initiative . 4 1.3.6 Health Policy . 4 1.3.7 Primary Health Care Service Development Programme (2007-2017) . 5 1.3.8 Health Sector Strategic Plan III (2009-2015). 6 1.3.9 The National Road Map Strategic Plan to Accelerate Reduction of Maternal, Newborn, and Child Deaths in Tanzania-One Plan (2008-2015) . 6 1.3.10 The Sharpened One Plan to Accelerate Progress (2014-2015) . 7 1.3.11 National Nutrition Strategy . 8 1.4 Strategic Direction for the Period 2015 to 2020 . 9 1.4.1 Health Sector Strategic Plan IV (2015-2020) . 9 1.4.2 One Plan II (2016-2020) . 10 1.4.3 National Key Result Area in Health Care . 11 1.5 Objectives and Survey Organization . 12 1.5.1 Objectives . 12 1.5.2 Survey Organization . 13 1.6 Fieldwork . 16 1.6.1 2015-16 TDHS-MIS Field Challenges . 17 1.6.2 Data Processing . 18 1.6.3 Response Rates . 18 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 21 2.1 Drinking Water Sources and Treatment . 22 2.2 Sanitation . 23 2.3 Exposure to Smoke inside the Home . 23 2.4 Housing Characteristics . 23 2.5 Household Wealth . 24 2.6 Hand Washing . 25 2.7 Household Population and Composition . 25 2.9 Birth Registration . 26 iv • Contents 2.10 Education . 26 2.10.1 Educational Attainment . 27 2.10.2 School Attendance . 27 2.11 Household Food Security . 28 2.12 Health Expenditures . 29 3 CHARACTERISTICS OF RESPONDENTS . 51 3.1 Basic Characteristics of Survey Respondents . 51 3.2 Education and Literacy . 52 3.3 Exposure to Mass Media and Internet Usage . 53 3.4 Employment . 54 3.5 Occupation . 55 3.6 Type of Employment: Women . 56 3.7 Health Insurance Coverage . 56 3.8 Tobacco Smoking . 57 3.9 Daily Smoking . 57 3.10 Male Circumcision . 57 4 MARRIAGE AND SEXUAL ACTIVITY . 85 4.1 Marital Status . 85 4.2 Polygyny . 86 4.3 Age at First Marriage . 87 4.4 Age at First Sexual Intercourse . 88 4.5 Recent Sexual Activity . 89 4.6 Age at First Sexual Intercourse among Young People . 89 4.7 Premarital Sexual Intercourse and Condom Use during Premarital Sexual Intercourse among Youth . 90 5 FERTILITY . 105 5.1 Current Fertility . 106 5.2 Children Ever Born and Living . 107 5.3 Birth Intervals . 107 5.4 Insusceptibility to Pregnancy . 108 5.5 Age at First Birth . 109 5.6 Teenage Childbearing . 110 6 FERTILITY PREFERENCES . 119 6.1 Desire for Another Child . 120 6.2 Ideal Family Size . 121 6.3 Fertility Planning Status . 122 6.4 Wanted Fertility Rates . 123 7 FAMILY PLANNING . 131 7.1 Contraceptive Knowledge and Use . 132 7.2 Source of Modern Contraceptive Methods . 134 7.3 Informed Choice . 134 7.4 Discontinuation of Contraceptives . 135 7.5 Demand for Family Planning . 135 7.6 Contact of Nonusers with Family Planning Providers . 137 8 INFANT AND CHILD MORTALITY . 157 8.1 Data Quality . 158 8.2 Infant and Child Mortality . 159 8.3 Bio-demographic Risk Factors . 160 8.4 Perinatal Mortality . 161 8.5 High-risk Fertility Behaviour . 161 Contents • v 9 MATERNAL HEALTH CARE . 167 9.1 Antenatal Care Coverage and Content . 168 9.2 Timing and Number of ANC Visits. 169 9.3 Components of ANC Visits . 169 9.4 Protection against Neonatal Tetanus . 170 9.5 Delivery Services . 170 9.6 Skilled Assistance during Delivery . 172 9.7 Caesarean Section . 173 9.8 Postnatal Care for Mothers . 174 9.9 Postnatal Health Checks for Newborns . 175 9.9.1 Timing and Type of Provider . 175 9.9.2 Content of Newborn Care . 175 9.10 Problems in Accessing Health Care . 176 10 CHILD HEALTH . 193 10.1 Birth Weight . 193 10.2 Vaccination of Children . 194 10.3 Symptoms of Acute Respiratory Infection . 196 10.4 Fever . 197 10.5 Diarrhoeal Disease . 198 10.5.1 Prevalence of Diarrhoea . 198 10.5.2 Feeding Practices . 198 10.5.3 Treatment of Diarrhoea . 199 10.5.4 Knowledge of ORS Packets . 200 10.6 Disposal of Children’s Stools . 201 11 NUTRITION OF CHILDREN AND WOMEN . 221 11.1 Nutritional Status of Children . 221 11.1.1 Measurement of Nutritional Status among Young Children . 221 11.1.2 Data Collection . 223 11.1.3 Levels of Child Malnutrition . 223 11.2 Infant and Young Child Feeding Practices . 224 11.2.1 Initiation of Breastfeeding . 224 11.2.2 Exclusive Breastfeeding . 225 11.2.3 Median Duration of Breastfeeding . 226 11.2.4 Complementary Feeding . 226 11.2.5 Minimum Acceptable Diet . 227 11.3 Anaemia Prevalence in Children . 228 11.4 Women’s Nutritional Status . 230 11.5 Anaemia Prevalence in Women. 231 11.6 Presence of Iodised Salt in Households . 231 11.7 Micronutrient Intake and Supplementation among Children . 233 11.8 Micronutrient Intake among Mothers . 234 11.9 Urinary Iodine Concentration Among Women . 234 12 MALARIA . 261 12.1 Ownership of Insecticide-Treated Nets . 262 12.2 Indoor Residual Spraying . 264 12.3 ITN Coverage, Access to an ITN, and Household Use of ITNs . 265 12.4 Use of ITNs by Children and Pregnant Women . 267 12.5 Malaria in Pregnancy . 268 12.6 Case Management of Malaria in Children . 269 12.7 Prevalence of Low Haemoglobin in Children . 271 12.8 Prevalence of Malaria in Children . 271 vi • Contents 13 MALARIA KNOWLEDGE AND COMMUNICATION . 299 13.1 Recognition of Malaria as a Serious Health Problem . 299 13.2 Knowledge of Malaria Signs or Symptoms . 300 13.3 Knowledge of Malaria Prevention . 301 13.4 Access to Artemisinin-based Combination Therapy (ACTs) and Visits from Health Workers . 302 13.5 Exposure to Malaria Messages . 303 13.6 Attitudes towards Malaria . 304 14 ADULT AND MATERNAL MORTALITY . 317 14.1 Adult and Maternal Mortality Data . 317 14.1.1 Sibling Survival History . 317 14.1.2 Assessment of Data Quality . 318 14.1.3 Assessment of Trends in Maternal Mortality . 318 14.2 Direct Estimates of Adult Mortality . 319 14.3 Direct Estimates of Maternal Mortality . 320 15 WOMEN’S EMPOWERMENT . 325 15.1 Married Women’s and Men’s Employment . 326 15.2 Control over Women’s Earnings . 326 15.3 Control over Men’s Earnings . 327 15.4 Women’s and Men’s Ownership of Assets . 328 15.5. Ownership and Use of Bank Accounts and Mobile Phones . 328 15.6 Women’s Participation in Decision Making . 329 15.7 Attitudes towards Wife Beating . 330 16 FEMALE GENITAL CUTTING . 357 16.1 Knowledge of FGC/M . 358 16.2 Prevalence of and Age at Circumcision among Women . 358 16.2.1 Prevalence and Type of FGC/M . 358 16.2.2 Age at Circumcision . 360 16.3 Prevalence of and Age at Circumcision for Girls Age 0-14 . 360 16.4 Opinions about FGC/M . 361 17 DOMESTIC VIOLENCE . 367 17.1 Measurement of Violence . 368 17.2 Experience of Physical Violence from Anyone . 368 17.2.1 Prevalence of Physical Violence . 368 17.2.2 Perpetrators of Physical Violence . 369 17.3 Experience of Sexual Violence . 369 17.3.1 Prevalence of Sexual Violence . 369 17.3.2 Perpetrators of Sexual Violence . 370 17.4 Experience of Different Forms of Violence . 370 17.5 Marital Control . 370 17.6 Spousal Violence . 371 17.7 Injuries due to Spousal Violence . 373 17.8 Violence Initiated by Women against Husbands/Partners . 373 17.9 Response to Violence . 374 17.9.1 Help Seeking Behaviour to Stop the Violence . 374 17.9.2 Sources for Help . 374 REFERENCES . 401 Contents • vii APPENDIX A SAMPLE DESIGN FOR THE 2015-16 TANZANIA DHS-MIS . 405 APPENDIX B ESTIMATES OF SAMPLING ERRORS . 413 APPENDIX C DATA QUALITY TABLES . 439 APPENDIX D PERSONS INVOLVED IN THE 2015-16 TANZANIA DHS-MIS . 443 APPENDIX E QUESTIONNAIRES . 449 APPENDIX F ADDITIONAL DHS PROGRAM RESOURCES . 591 Tables and Figures • ix TABLES AND FIGURES 1 INTRODUCTION AND SURVEY METHODOLOGY . 1 Table 1.1 Selected demographic indicators from various sources, Tanzania 1967-2012 . 19 Table 1.2 Results of the household and individual interviews . 19 2 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION . 21 Table 2.1 Household drinking water . 31 Table 2.2 Availability of water . 32 Table 2.3 Household sanitation facilities . 32 Table 2.4 Household characteristics . 33 Table 2.5 Household possessions . 34 Table 2.6 Wealth quintiles . 35 Table 2.7 Hand washing . 36 Table 2.8 Household population by age, sex, and residence . 37 Table 2.9 Household composition . 37 Table 2.10 Children’s living arrangements and orphanhood . 38 Table 2.11 Birth registration of children under age 5 . 40 Table 2.12 School attendance by survivorship of parents . 41 Table 2.13.1 Educational attainment of the female household population . 42 Table 2.13.2 Educational attainment of the male household population . 43 Table 2.14 School attendance ratios . 44 Table 2.15 Household food security . 46 Table 2.16 Annual outpatient visits and inpatient admissions . 47 Table 2.17 Annual per capita expenditure (in TZS) outpatient visits and inpatient admissions . 48 Table 2.18 Annual total health expenditure (in TZS) per household . 49 Figure 2.1 Household drinking water by residence . 22 Figure 2.2 Household toilet facilities by residence . 23 Figure 2.3 Household wealth by residence. 24 Figure 2.4 Population pyramid . 25 Figure 2.5 Orphanhood by age . 26 Figure 2.6 Primary and secondary school attendance by wealth quintile . 28 Figure 2.7 Per capita expenditure by household wealth quintile . 29 3 CHARACTERISTICS OF RESPONDENTS . 51 Table 3.1 Background characteristics of respondents . 59 Table 3.2.1 Educational attainment: Women . 61 Table 3.2.2 Educational attainment: Men . 62 Table 3.3.1 Literacy: Women . 63 Table 3.3.2 Literacy: Men . 63 Table 3.4.1 Exposure to mass media: Women . 65 Table 3.4.2 Exposure to mass media: Men . 66 Table 3.5.1 Internet usage: Women . 67 Table 3.5.2 Internet usage: Men . 68 Table 3.6.1 Employment status: Women . 69 Table 3.6.2 Employment status: Men . 71 Table 3.7.1 Occupation: Women . 73 x • Tables and Figures Table 3.7.2 Occupation: Men . 75 Table 3.8 Type of employment: Women . 76 Table 3.9.1 Health insurance coverage: Women . 77 Table 3.9.2 Health insurance coverage: Men . 78 Table 3.10 Tobacco smoking . 79 Table 3.11 Average number of cigarettes smoked daily: Men . 81 Table 3.12 Male circumcision . 82 Table 3.13 Prevalence of medical injections . 83 Figure 3.1 Education of survey respondents . 52 Figure 3.2 Exposure to mass media . 54 Figure 3.3 Employment status by education . 54 Figure 3.4 Occupation . 55 4 MARRIAGE AND SEXUAL ACTIVITY . 85 Table 4.1 Current marital status . 91 Table 4.2.1 Number of women’s co-wives . 92 Table 4.2.2 Number of men’s wives . 93 Table 4.3 Age at first marriage . 94 Table 4.4 Median age at first marriage by background characteristics . 95 Table 4.5 Age at first sexual intercourse . 96 Table 4.6 Median age at first sexual intercourse by background characteristics . 97 Table 4.7.1 Recent sexual activity: Women . 98 Table 4.7.2 Recent sexual activity: Men . 100 Table 4.8 Age at first sexual intercourse among young people . 102 Table 4.9 Premarital sexual intercourse and condom use during premarital sexual intercourse among youth . 103 Figure 4.1 Marital status . 86 Figure 4.2 Median age at first sex and first marriage among women and men . 88 Figure 4.3 Sexual intercourse among youth age 15 24 by marital status . 89 5 FERTILITY . 105 Table 5.1 Current fertility . 112 Table 5.2 Fertility by background characteristics . 112 Table 5.3.1 Trends in age-specific fertility rates . 113 Table 5.3.2 Trends in age-specific and total fertility rates . 113 Table 5.4 Children ever born and living . 113 Table 5.5 Birth intervals . 114 Table 5.6 Postpartum amenorrhea, abstinence and insusceptibility . 115 Table 5.7 Median duration of amenorrhea, postpartum abstinence and postpartum insusceptibility . 116 Table 5.8 Menopause . 116 Table 5.9 Age at first birth . 117 Table 5.10 Median age at first birth . 117 Table 5.11 Teenage pregnancy and motherhood . 118 Figure 5.1 Trends fertility by residence . 106 Figure 5.2 Fertility by zone . 106 Figure 5.3 Total fertility rate by wealth index . 107 Figure 5.4 Trends in birth interval . 107 Figure 5.5 Median age at first birth by education . 110 Figure 5.6 Teenage childbearing by region . 111 Tables and Figures • xi 6 FERTILITY PREFERENCES . 119 Table 6.1 Fertility preferences by number of living children . 125 Table 6.2 Desire to limit childbearing . 126 Table 6.3 Ideal number of children by number of living children . 127 Table 6.4 Mean ideal number of children . 128 Table 6.5 Fertility planning status . 129 Table 6.6 Wanted fertility rates . 130 Figure 6.1 Desire for more children among married women . 120 Figure 6.2 Trends in desire to limit childbearing . 120 Figure 6.3 Ideal family size . 121 Figure 6.4 Ideal family size . 121 Figure 6.5 Ideal family size by number of living children . 122 Figure 6.6 Fertility planning status . 123 Figure 6.7 Trends in wanted and actual fertility . 123 7 FAMILY PLANNING . 131 Table 7.1 Knowledge of contraceptive methods . 139 Table 7.2 Knowledge of contraceptive methods by background characteristics . 140 Table 7.3 Current use of contraception by age . 141 Table 7.4.1 Trends in the current use of contraception . 142 Table 7.4.2 Current use of contraception by background characteristics . 143 Table 7.5.1 Timing of sterilisation . 144 Table 7.5.2 Timing of modern contraceptive use after birth . 144 Table 7.6 Source of modern contraception methods . 145 Table 7.7 Use of social marketing brand pills and condoms . 145 Table 7.8 Informed choice . 146 Table 7.9 Twelve-month contraceptive discontinuation rates . 146 Table 7.10 Reasons for discontinuation . 147 Table 7.11 Knowledge of fertile period . 147 Table 7.12.1 Need and demand for family planning among currently married women . 148 Table 7.12.2 Need and demand for family planning for all women and for women who are not currently married . 150 Table 7.13 Future use of contraception . 152 Table 7.14 Exposure to family planning messages . 152 Table 7.15 Contact of nonusers with family planning providers . 154 Figure 7.1 Contraceptive use . 132 Figure 7.2 Trends of contraceptive use from 1991-92 to 2015 16 . 132 Figure 7.3 Modern contraceptive use by region . 133 Figure 7.4 Modern contraceptive use by education . 133 Figure 7.5 Source of modern contraceptive methods . 134 Figure 7.6 Demand for family planning . 136 Figure 7.7 Trends in demand for family planning . 136 Figure 7.8 Unmet need by region . 137 8 INFANT AND CHILD MORTALITY . 157 Table 8.1 Early childhood mortality rates . 163 Table 8.2 Early childhood mortality rates by socioeconomic characteristics . 163 Table 8.3 Early childhood mortality rates by demographic characteristics . 164 Table 8.4 Perinatal mortality . 165 Table 8.5 High-risk fertility behaviour . 166 Figure 8.1 Trends in early childhood mortality . 160 xii • Tables and Figures 9 MATERNAL HEALTH CARE . 167 Table 9.1 Antenatal care . 177 Table 9.2 Number of antenatal care visits and timing of first visit . 178 Table 9.3 Components of antenatal care . 179 Table 9.4 Tetanus toxoid injections . 180 Table 9.5 Place of delivery . 181 Table 9.6 Assistance during delivery . 182 Table 9.7 Caesarean section . 185 Table 9.8 Timing of first postnatal checkup . 187 Table 9.9 Type of provider of first postnatal checkup for the mother . 188 Table 9.10 Timing of first postnatal checkup for the newborn . 189 Table 9.11 Type of provider of first postnatal checkup for the newborn . 190 Table 9.12 Content of postnatal care for newborns . 191 Table 9.13 Problems in accessing health care . 192 Figure 9.1 Antenatal care coverage . 168 Figure 9.2 Components of antenatal care . 169 Figure 9.3 Trends in institutional deliveries . 171 Figure 9.4 Institutional deliveries by region . 171 Figure 9.5 Institutional deliveries by mother's education . 172 Figure 9.6 Assistance during delivery . 172 Figure 9.7 Skilled assistance at delivery by region . 173 Figure 9.8 Skilled assistance at delivery by wealth quintile . 173 Figure 9.9 Postnatal care for mothers by birth order . 174 10 CHILD HEALTH . 193 Table 10.1 Child’s size and weight at birth. 203 Table 10.2 Vaccinations by source of information . 205 Table 10.3 Vaccinations by background characteristics . 206 Table 10.4 Possession and observation of vaccination cards, according to background characteristics . 208 Table 10.5 Prevalence and treatment of symptoms of ARI . 210 Table 10.6 Prevalence and treatment of fever . 211 Table 10.7.1 Prevalence of diarrhoea . 213 Table 10.7.2 Feeding practices during diarrhoea . 215 Table 10.8 Diarrhoea treatment . 216 Table 10.9 Knowledge of ORS packets or pre-packaged liquids. 218 Table 10.10 Disposal of children’s stools . 219 Figure 10.1 Childhood vaccinations . 195 Figure 10.2 Trends in childhood vaccinations . 195 Figure 10.3 Vaccination coverage by region . 196 Figure 10.4 Diarrhoea prevalence by age . 198 Figure 10.5 Feeding practices during diarrhoea . 199 Figure 10.6 Treatment of diarrhoea . 200 Figure 10.7 Prevalence and treatment of childhood illnesses . 201 11 NUTRITION OF CHILDREN AND WOMEN . 221 Table 11.1 Nutritional status of children . 237 Table 11.2 Initial breastfeeding . 239 Table 11.3.1 Breastfeeding status by age . 240 Table 11.3.2 Breastfeeding status by background characteristics . 241 Table 11.4 Median duration of breastfeeding . 242 Tables and Figures • xiii Table 11.5 Foods and liquids consumed by children in the day or night preceding the interview . 243 Table 11.6 Infant and young child feeding (IYCF) practices . 244 Table 11.7 Prevalence of anaemia in children . 246 Table 11.8 Nutritional status of women . 248 Table 11.9 Prevalence of anaemia in women . 250 Table 11.10 Presence of iodised salt in household: Rapid test . 252 Table 11.11 Coverage of laboratory salt collection for laboratory testing . 253 Table 11.12 Household iodine levels: Laboratory testing . 254 Table 11.13 Micronutrient intake among children . 255 Table 11.14 Micronutrient intake among mothers . 257 Table 11.15 Coverage of urine collection for women by residence and region for women . 259 Table 11.16 Urinary iodine concentrations in women . 260 Figure 11.1 Children’s nutritional status . 223 Figure 11.2 Trends in nutritional status of children . 223 Figure 11.3 Stunting in children by region . 224 Figure 11.4 Breastfeeding practices by age . 225 Figure 11.5 IYCF breastfeeding indicators . 226 Figure 11.6 IYCF indicators on minimum acceptable diet (MAD). 228 Figure 11.7 Trends in childhood anaemia . 229 Figure 11.8 Anaemia in children by region . 229 Figure 11.9 Trends in women’s nutritional status . 230 Figure 11.10 Trends in anaemia status among women . 231 Figure 11.11 Presence of iodised salt among households in which salt was tested by region . 232 Figure 11.12 Urinary iodine concentrations in women by region . 235 12 MALARIA . 261 Table 12.1 Household possession of mosquito nets . 274 Table 12.2 Source of mosquito nets . 275 Table 12.3 Indoor residual spraying against mosquitoes . 276 Table 12.4.1 Access to an insecticide-treated net (ITN) . 277 Table 12.4.2 Access to an insecticide-treated net (ITN) according to background characteristics . 278 Table 12.5 Use of mosquito nets by persons in the household . 279 Table 12.6 Use of existing ITNs . 281 Table 12.7 Reason for not using mosquito nets . 282 Table 12.8 Use of mosquito nets by children . 283 Table 12.9 Use of mosquito nets by pregnant women . 285 Table 12.10 Use of Intermittent Preventive Treatment (IPTp) by women during pregnancy . 286 Table 12.11 Prevalence, diagnosis, and prompt treatment of children with fever . 287 Table 12.12.1 Source of advice or treatment for children with fever . 289 Table 12.12.2 Children with fever who took antimalarial drugs . 290 Table 12.13.1 Type of antimalarial drugs used . 291 Table 12.13.2 Timing of antimalarial drugs used . 291 Table 12.14 Coverage of testing for haemoglobin level and malaria in children . 292 Table 12.15 Haemoglobin <8.0 g/dl in children . 294 Table 12.16 Malaria prevalence among children according to a rapid diagnostic test (RDT) and microscopy . 296 xiv • Tables and Figures Figure 12.1 Source of ITNs . 263 Figure 12.2 Trends in household ownership of ITNs . 263 Figure 12.3 ITN ownership by region . 264 Figure 12.4 Ownership of, access to, and use of ITNs . 265 Figure 12.5 Trend in ITN use . 266 Figure 12.6 Household possession of mosquito nets by region . 266 Figure 12.7 Trend in use of ITNs by children under age 5 and pregnant women . 267 Figure 12.8 Trends in IPTp use by pregnant women . 269 Figure 12.9 Trend in ACT use by children with fever . 270 Figure 12.10 Haemoglobin <8.0 g/dl in children age 6-59 months by region . 271 Figure 12.11 Prevalence of malaria in children by region . 272 13 MALARIA KNOWLEDGE AND COMMUNICATION . 299 Table 13.1.1 Most serious health problem in community: Women . 306 Table 13.1.2 Most serious health problem in community: Men . 307 Table 13.2.1 Knowledge of malaria symptoms: Women . 308 Table 13.2.2 Knowledge of malaria symptoms: Men . 309 Table 13.3.1 Knowledge of ways to avoid malaria: Women . 310 Table 13.3.2 Knowledge of ways to avoid malaria: Men . 311 Table 13.4.1 Access to ACTs, messages about malaria prevention and treatment, and visits from health workers: Women . 312 Table 13.4.2 Access to ACTs, messages about malaria prevention and treatment, and visits from health workers: Men . 313 Table 13.5.1 Media exposure to malaria messages: Women . 314 Table 13.5.2 Media exposure to malaria messages: Men . 315 Table 13.6 Women’s attitude towards malaria . 316 Figure 13.1 Trends in the percent distribution of women and men by the most serious health problem in the community . 300 Figure 13.2 Malaria signs and symptoms in young children . 301 Figure 13.3 Knowledge of malaria prevention . 302 Figure 13.4 Access to ACTs and malaria information . 303 Figure 13.5 Source of malaria messages . 304 Figure 13.6 Trends in attitudes about malaria . 305 14 ADULT AND MATERNAL MORTALITY . 317 Table 14.1 Completeness of information on siblings . 322 Table 14.2 Sibship size and sex ratio of siblings . 322 Table 14.3 Adult mortality rates . 322 Table 14.4 Adult mortality probabilities . 323 Table 14.5 Maternal mortality . 323 Figure 14.1 Adult mortality rates by age . 319 Figure 14.2 Trends in adult mortality . 320 Figure 14.3 Trends in maternal mortality ratios with confidence intervals . 321 15 WOMEN’S EMPOWERMENT . 325 Table 15.1 Employment and cash earnings of currently married women and men . 332 Table 15.2.1 Control over women’s cash earnings and relative magnitude of women’s cash earnings . 333 Table 15.2.2 Control over men’s cash earnings . 335 Table 15.3 Women’s control over their own earnings and over those of their husbands . 336 Table 15.4.1 Ownership of assets: Women . 337 Tables and Figures • xv Table 15.4.2 Ownership of assets: Men . 338 Table 15.5.1 Ownership of title or deed for house: Women . 339 Table 15.5.2 Ownership of title or deed for house: Men . 340 Table 15.6.1 Ownership of title or deed for land: Women . 341 Table 15.6.2 Ownership of title or deed for land: Men . 342 Table 15.7.1 Ownership and use of bank accounts and mobile phones: Women . 343 Table 15.7.2 Ownership and use of bank accounts and mobile phones: Men . 344 Table 15.8 Participation in decision making . 345 Table 15.9.1 Women’s participation in decision making by background characteristics . 346 Table 15.9.2 Men’s participation in decision making by background characteristics . 348 Table 15.10.1 Attitude toward wife beating: Women . 350 Table 15.10.2 Attitude toward wife beating: Men . 352 Table 15.11 Indicators of women’s empowerment . 354 Table 15.12 Current use of contraception by women’s empowerment . 354 Table 15.13 Ideal number of children and unmet need for family planning by women’s empowerment . 355 Table 15.14 Reproductive health care by women’s empowerment . 355 Table 15.15 Early childhood mortality rates by indicators of women’s empowerment . 355 Figure 15.1 Employment by age among currently married women and men . 326 Figure 15.2 Control over women’s earnings . 327 Figure 15.3 Ownership of assets . 328 Figure 15.4 Women’s participation in decision making. 329 Figure 15.5 Attitudes towards wife beating . 330 16 FEMALE GENITAL CUTTING . 357 Table 16.1 Knowledge of female circumcision . 362 Table 16.2 Prevalence of female circumcision . 363 Table 16.3 Age at circumcision . 364 Table 16.4 Prevalence of circumcision and age at circumcision: girls age 0-14 . 364 Table 16.5 Opinions of women about whether circumcision is required by religion . 365 Table 16.6 Opinions of women about whether the practice of circumcision should continue . 366 Figure 16.1 Type of FGC/M . 359 Figure 16.2 Trends in FGC/M . 359 Figure 16.3 FGC/M by age . 359 Figure 16.4 Prevalence of FGC/M by region . 360 Figure 16.5 Attitudes about FGC/M by circumcision status . 361 17 DOMESTIC VIOLENCE . 367 Table 17.1 Experience of physical violence . 376 Table 17.2 Experience of violence during pregnancy . 378 Table 17.3 Persons committing physical violence . 380 Table 17.4 Experience of sexual violence. 381 Table 17.5 Age at first experience of sexual violence . 383 Table 17.6 Persons committing sexual violence . 383 Table 17.7 Experience of different forms of violence . 384 Table 17.8 Marital control exercised by husbands . 385 Table 17.9 Forms of spousal violence . 387 Table 17.10 Physical or sexual violence in the past 12 months by any husband/partner . 388 Table 17.11 Spousal violence by background characteristics . 390 Table 17.12 Spousal violence by husband’s characteristics and empowerment indicators . 392 xvi • Tables and Figures Table 17.13 Experience of spousal violence by duration of marriage . 393 Table 17.14 Injuries to women due to spousal violence . 394 Table 17.15 Women’s violence against their spouse by background characteristics . 395 Table 17.16 Women’s violence against their spouse by husband’s characteristics and empowerment indicators . 397 Table 17.17 Help seeking to stop violence . 398 Table 17.18 Sources for help to stop the violence . 399 Table 17.19 Frequency of spousal violence among those who report violence . 400 Figure 17.1 Violence during pregnancy by number of living children . 368 Figure 17.2 Women’s experience of physical or sexual violence by marital status . 369 Figure 17.3 Types of spousal violence . 371 Figure 17.4 Spousal violence by region . 372 Figure 17.5 Spousal violence by husband’s alcohol consumption . 373 Figure 17.6 Help seeking by type of violence experienced . 374 APPENDIX A SAMPLE DESIGN FOR THE 2015-16 TANZANIA DHS-MIS . 405 Table A.1 Distribution of residential households by region and according to type of residence . 406 Table A.2 Distribution of EAs and their average size in number of households by region and according to type of residence. 407 Table A.3 Sample allocation of EAs and households by region and according to type of residence . 408 Table A.4 Sample allocation of expected number of interviews by region and according to type of residence . 409 Table A.5 Sample implementation: Women . 411 Table A.6 Sample implementation: Men . 412 APPENDIX B ESTIMATES OF SAMPLING ERRORS . 413 Table B.1 List of selected variables for sampling errors, Tanzania DHS 2015 . 415 Table B.2 Sampling errors: Total sample, Tanzania 2015-16 . 416 Table B.3 Sampling errors: Urban sample, Tanzania 2015-16 . 417 Table B.4 Sampling errors: Rural sample, Tanzania 2015-16 . 418 Table B.5 Sampling errors: Tanzania Mainland sample, Tanzania 2015-16 . 419 Table B.6 Sampling errors: Mainland urban sample, Tanzania 2015-16 . 420 Table B.7 Sampling errors: Mainland rural sample, Tanzania 2015-16 . 421 Table B.8 Sampling errors: Zanzibar sample, Tanzania 2015-16 . 422 Table B.9 Sampling errors: Unguja (Zanzibar Island) sample, Tanzania 2015-16 . 423 Table B.10 Sampling errors: Pemba (Pemba Island) sample, Tanzania 2015-16 . 424 Table B.11 Sampling errors: Western sample, Tanzania 2015-16 . 425 Table B.12 Sampling errors: Northern sample, Tanzania 2015-16 . 426 Table B.13 Sampling errors: Central sample, Tanzania 2015-16 . 427 Table B.14 Sampling errors: Southern Highlands sample, Tanzania 2015-16 . 428 Table B.15 Sampling errors: Southern sample, Tanzania 2015-16 . 429 Table B.16 Sampling errors: South West Highlands sample, Tanzania 2015-16 . 430 Table B.17 Sampling errors: Lake sample, Tanzania 2015-16 . 431 Table B.18 Sampling errors: Eastern sample, Tanzania 2015-16 . 432 Table B.19 Sampling errors: Zanzibar sample, Tanzania 2015-16 . 433 Table B.20 Sampling errors for adult and maternal mortality rates, Tanzania DHS 2015 . 434 Table B.21 Sampling errors: Total sample . 435 Table B.22 Sampling errors: Urban sample. 435 Table B.23 Sampling errors: Rural sample . 435 Table B.24 Sampling errors: Tanzania Mainland sample . 435 Tables and Figures • xvii Table B.25 Sampling errors: Mainland urban sample . 435 Table B.26 Sampling errors: Mainland rural sample . 436 Table B.27 Sampling errors: Zanzibar sample . 436 Table B.28 Sampling errors: Unguja (Zanzibar Island) sample . 436 Table B.29 Sampling errors: Pemba (Pemba Island) sample . 436 Table B.30 Sampling errors: Western sample . 436 Table B.31 Sampling errors: Northern sample . 437 Table B.32 Sampling errors: Central sample . 437 Table B.33 Sampling errors: Southern Highlands sample . 437 Table B.34 Sampling errors: Southern sample . 437 Table B.35 Sampling errors: South West Highlands sample . 437 Table B.36 Sampling errors: Lake sample. 438 Table B.37 Sampling errors: Eastern sample . 438 Table B.38 Sampling errors: Zanzibar sample . 438 APPENDIX C DATA QUALITY TABLES . 439 Table C.1 Household age distribution . 439 Table C.2.1 Age distribution of eligible and interviewed women . 440 Table C.2.2 Age distribution of eligible and interviewed men . 440 Table C.3 Completeness of reporting . 440 Table C.4 Births by calendar years . 441 Table C.5 Reporting of age at death in days . 441 Table C.6 Reporting of age at death in months . 442 Foreword • xix FOREWORD he 2015-16 Tanzania Demographic and Health Survey and Malaria Indicator Survey (TDHS-MIS) is the sixth in a series of DHS surveys conducted in Tanzania. The National Bureau of Statistics (NBS), Tanzania Mainland, and Office of the Chief Government Statistician (OCGS), Zanzibar, conducted the survey in collaboration with the Ministry of Health, Community Development, Gender, Elderly and Children (MoHCDGEC), Tanzania Mainland, and the Ministry of Health (MoH), Zanzibar. The 2015-16 TDHS-MIS follows up the previous surveys conducted in 1991-92, 1996, 1999, 2004-05, and 2010. The availability of data and reports from these surveys provides an opportunity for trend analysis of the several population and health indicators covered in these surveys and identified in the related country’s development agenda. The main objective of the 2015-16 TDHS-MIS was to obtain the current and reliable information on demographic and health indicators with regard to family planning, fertility levels and preferences, maternal mortality, infant and child mortality, nutritional status of mothers and children, antenatal care, delivery care, and childhood immunizations and diseases. In addition, the survey was designed to provide up-to- date information on the prevalence of anaemia among women age 15-49 and the prevalence of malaria infection and anaemia among children under age 5. Unlike the previous DHS surveys, the 2015-16 TDHS- MIS included a comprehensive module on malaria, which is usually included in the Tanzania HIV and Malaria Indicators surveys. This survey did not include questions and tests on HIV/AIDS because they will certainly be included in future HIV/AIDS surveys. The 2015-16 TDHS-MIS was implemented with financial support from various donors, including the Government of Tanzania, Global Affairs Canada, the United States Agency for International Development (USAID), Irish Aid, the United Nations Population Fund (UNFPA), and the United Nations Children’s Fund (UNICEF). Technical assistance was provided by ICF International through The Demographic and Health Surveys Program (The DHS Program) and also by the Technical Committee of the 2015-16 TDHS- MIS. This report presents the detailed findings from the 2015-16 TDHS-MIS at national, zonal (as used by the MoHCDGEC), and where possible, regional levels. The report provides useful information for assessing the country’s performance on some of the health and population indicators included in the previous national and international development agendas, for example, the National Strategy for Growth and Reduction of Poverty II, NSGRP or MKUKUTA II, Health Sector Strategic Plan III (2010-2015), and the 2015 Millennium Development Goals (MDGs). At the same time, the 2015-16 TDHS-MIS will provide the baseline information for measuring progress of the health- and population-related indicators that are included in the national and international development agendas, including Health Sector Strategic Plan IV (2015-2020), the Five-Year Development Plans (2016/17-2020/21), and the 2030 Agenda for Sustainable Development. I, therefore, take this opportunity to encourage policy makers, planners, program managers, and other stakeholders in the health sector to use these findings for making informed policy decisions based on quality planning, monitoring, and evaluating programmes related to reproductive health. Furthermore, such initiatives aim at facilitating the proper delivery of various health and social services in general. Finally, I also advise researchers and other experts to undertake further analysis of the available data sets, particularly in the areas that are not covered in this report. It is expected that the analysed data will ultimately be made available for use by the relevant stakeholders and the general public. Dr. Mpoki M. Ulisubisya Permanent Secretary Ministry of Health, Community Development, Gender, Elderly and Children T Acknowledgements • xxi ACKNOWLEDGEMENTS he successful completion of the 2015-16 Tanzania Demographic and Health Survey and Malaria Indicator Survey (TDHS-MIS) was enabled by the collaborative efforts of various institutions and individuals whose contribution is highly appreciated. Initially, the National Bureau of Statistics (NBS) wishes to extend its sincere gratitude to the Government of Tanzania, Global Affairs Canada, the United States Agency for International Development (USAID), Irish Aid, the United Nations Population Fund (UNFPA),and the United Nations Children’s Fund (UNICEF) for providing financial assistance that led to the smooth implementation of the 2015-16 TDHS- MIS. We would like to thank a team from ICF International for their technical assistance provided in all stages from the preparation and implementation of this survey. We gratefully acknowledge the guidance and support of the survey’s Technical Committee (TC) members who came from various organizations, including the Ministry of Health, Community Development, Gender, Elderly and Children (MoHCDGEC)–Tanzania Mainland; Ministry of Health–Zanzibar; National Bureau of Standards (NBS); Office of the Chief Government Statistician (OCGS); Tanzania Food and Nutrition Centre (TFNC); National Malaria Control Program (NMCP); World Health Organization (WHO); National Institute for Medical Research (NIMR), Zanzibar Malaria Elimination Programme (ZAMEP); The World Bank (WB); UNICEF; USAID; UNFPA; Irish Aid; and Ifakara Health Institute (IHI). We also recognize the contribution of the staff of Ifakara Health Institute Laboratories at Bagamoyo and TFNC Laboratories at Mikocheni–Dar es Salaam, who conducted laboratory microscopic analysis of malaria and urinary iodine and salt iodine tests, respectively. We also wish to express our deep appreciation for commendable work done by the authors, reviewers, and editors of this report from different institutions. The nurses from the ministry responsible for health from both Tanzania Mainland and Tanzania Zanzibar who worked tirelessly as interviewers; staff from NBS and OCGS who worked as field supervisors; and other field staff including field editors, office editors, and teams’ drivers deserve our heartfelt gratitude for their dedicated and tireless effort in making this survey a success. Last but not least, we are even more grateful to the local leaders in the areas visited for data collection for their co-operation as well as the survey respondents for their willingness and patience in providing appropriate information that enabled the data analysts, chapter writers, and statistical consultants among others to finalize this report. Dr. Albina Chuwa Director General National Bureau of Statistics T Reading and Understanding Tables from the 2015 TDHS-MIS • xxiii READING AND UNDERSTANDING TABLES FROM THE 2015 TDHS-MIS he DHS final report is based on approximately 200 tables of data. Although the text and figures featured in each chapter highlight some of the most important findings from the tables, not every finding can be discussed or displayed graphically. For this reason, DHS data users should be comfortable reading and interpreting tables. The following pages provide an introduction to the organization of DHS tables, the presentation of background characteristics, and a brief summary of sampling and understanding denominators. In addition, this section provides some exercises to allow users to practice their new skills in interpreting DHS tables. T xxiv • Reading and Understanding Tables from the 2015 TDHS-MIS Example 1: Exposure to Mass Media A Question Asked of All Survey Respondents Table 3.4.1 Exposure to mass media: Women Percentage of women age 15-49 who are exposed to specific media on a weekly basis, by background characteristics, Tanzania DHS-MIS 2015-16 Background characteristic Reads a newspaper at least once a week Watches television at least once a week Listens to the radio at least once a week Accesses all three media at least once a week Accesses none of the three media at least once a week Number of women Age 15-19 16.3 31.3 43.2 8.4 43.3 2,904 20-24 15.1 30.5 48.9 8.9 41.4 2,483 25-29 13.6 29.1 47.7 8.6 44.0 2,125 30-34 11.1 26.4 44.5 6.8 47.4 1,752 35-39 11.0 23.0 42.8 5.5 49.3 1,641 40-44 10.6 20.2 40.6 6.1 52.8 1,364 45-49 11.3 16.9 40.6 4.7 54.4 997 Residence Urban 22.0 54.8 56.2 15.8 26.4 4,811 Rural 8.4 11.0 38.0 2.7 57.4 8,455 Tanzania Mainland/Zanzibar Mainland 13.4 26.3 44.4 7.5 46.5 12,862 Urban 22.2 54.5 56.2 15.9 26.6 4,675 Rural 8.4 10.2 37.7 2.7 57.9 8,187 Zanzibar 10.7 45.4 52.2 6.8 33.8 404 Unguja 12.8 57.7 66.7 8.6 17.4 293 Pemba 5.2 13.3 14.3 2.2 76.9 111 Zone Western 8.0 13.6 38.5 3.7 56.4 1,278 Northern 18.5 40.3 55.6 10.2 30.7 1,575 Central 9.4 11.0 32.0 3.1 62.1 1,336 Southern Highlands 9.3 22.4 39.8 6.4 54.6 807 Southern 7.1 14.6 40.1 3.0 55.0 700 South West Highlands 18.5 19.7 40.3 8.0 52.2 1,246 Lake 8.4 18.0 42.5 4.1 51.6 3,463 Eastern 22.9 52.0 54.6 16.3 28.0 2,457 Zanzibar 10.7 45.4 52.2 6.8 33.8 404 Region Dodoma 7.2 7.6 23.0 1.5 71.6 572 Arusha 16.0 37.3 54.7 7.8 33.1 508 Kilimanjaro 17.4 41.4 60.3 9.7 27.4 361 Tanga 21.0 41.9 53.9 12.3 30.6 706 Morogoro 21.3 28.7 52.2 11.4 38.8 636 Pwani 14.4 20.0 38.4 6.8 54.3 285 Dar Es Salaam 25.2 67.5 58.6 20.0 18.7 1,536 Lindi 6.4 14.9 30.2 2.1 62.7 288 Mtwara 7.5 14.5 46.9 3.6 49.7 412 Ruvuma 6.3 19.0 34.8 5.4 60.3 360 Iringa 19.0 29.4 40.6 11.5 52.1 245 Mbeya 18.1 18.9 39.1 7.7 53.7 828 Singida 12.5 15.4 43.7 5.0 51.1 370 Tabora 8.3 12.5 36.6 4.2 59.3 737 Rukwa 20.7 21.4 44.5 9.3 48.5 288 Kigoma 7.6 15.0 41.2 3.2 52.3 542 Shinyanga 8.0 19.0 42.6 3.5 50.0 504 Kagera 8.1 19.4 54.1 4.3 40.4 612 Mwanza 9.0 20.3 33.8 4.8 58.6 859 Mara 13.5 25.9 50.2 6.7 42.2 523 Manyara 9.8 11.8 33.9 3.5 58.7 394 Njombe 2.9 20.0 47.7 2.1 47.3 203 Katavi 16.3 21.6 38.4 6.7 51.0 130 Simiyu 2.1 8.7 32.6 1.0 64.5 479 Geita 8.6 11.6 44.1 3.2 52.6 485 Kaskazini Unguja 8.6 26.0 58.1 1.9 31.8 56 Kusini Unguja 3.2 35.1 70.3 1.6 22.8 35 Mjini Magharibi 15.7 70.5 68.4 11.7 12.4 201 Kaskazini Pemba 8.4 16.6 17.1 3.6 71.2 56 Kusini Pemba 1.9 9.8 11.5 0.7 82.8 55 (Continued….) 1 3 2 Reading and Understanding Tables from the 2015 TDHS-MIS • xxv Table 3.4.1—Continued Background characteristic Reads a newspaper at least once a week Watches television at least once a week Listens to the radio at least once a week Accesses all three media at least once a week Accesses none of the three media at least once a week Number of women Education No education 0.9 5.4 26.2 0.0 71.7 1,946 Primary incomplete 4.4 11.8 36.1 1.3 58.4 1,559 Primary complete 12.5 23.7 44.4 5.8 46.9 6,652 Secondary+ 27.3 54.8 61.0 18.8 22.4 3,109 Wealth quintile Lowest 4.8 2.1 22.5 0.6 75.1 2,239 Second 5.8 4.0 31.4 0.9 65.5 2,281 Middle 8.4 6.7 42.6 1.8 53.5 2,314 Fourth 14.3 20.8 50.3 5.7 42.2 2,826 Highest 25.9 74.5 63.6 20.9 14.3 3,606 Total 13.3 26.9 44.6 7.5 46.1 13,266 Step 1: Read the title and subtitle. They tell you the topic and the specific population group being described. In this case, the table is about women age 15-49 and their access to different types of media. All eligible female respondents age 15-49 were asked these questions. Step 2: Scan the column headings—highlighted in green in the table on the left and above. They describe how the information is categorized. In this table, the first three columns of data show different types of media that women access at least once a week. The fourth column shows women who access all three media, while the fifth column is women who do not access any of the three types of media at least once a week. The last column lists the number of women interviewed in the survey. Step 3: Scan the row headings—the first vertical column highlighted in blue in the table above. These show the different ways the data are divided into categories based on population characteristics. In this case, the table presents women’s access to media by age, urban and rural residence, Tanzania Mainland/Zanzibar, zone, region, education level, and wealth quintile. Most of the tables in the TDHS- MIS report will be divided into these same categories. Step 4: Look at the row at the bottom of the table highlighted in red. These percentages represent the totals of all women age 15-49 and their access to different types of media. In this case, 13.3% of women age 15- 49 read a newspaper at least once a week, 26.9% watch television weekly, and 44.6% listen to the radio weekly. Step 5: To find out what percentage of women with secondary or higher education access all three media weekly, draw two imaginary lines, as shown on the table. This shows that 18.8% of women age 15-49 with secondary or higher education access all three types of media weekly. Practice: Use the table in Example 1 to answer the following questions: a) What percentage of women in Tanzania do not access any of the three media at least once a week? b) What age group of women are most likely to watch television weekly? c) Compare women in urban areas to women in rural areas—which group is more likely to listen to the radio weekly? Answers: a) 46.1% b) Women age 15-19: 31.3% of women in this age group watch television weekly c) Women in urban areas: 56.2% listen to the radio weekly, compared to 38.0% of women in rural areas 4 5 1 3 2 xxvi • Reading and Understanding Tables from the 2015 TDHS-MIS Example 2: Prevalence of Malaria in Children Comparing and Understanding Patterns Table 12.16 Malaria prevalence among children according to a rapid diagnostic test (RDT) and microscopy Percentage of children 6-59 months tested using a RDT who are positive for malaria and percentage of children 6-59 months tested using microscopy who are positive for malaria, by background characteristics, Tanzania DHS-MIS 2015-16 Malaria prevalence using a RDT Malaria prevalence using microscopy Background characteristic Tested positive Number of children tested Tested positive Number of children tested Age in months 6-8 8.4 517 4.3 483 9-11 8.4 454 1.3 424 12-17 10.3 1,104 4.1 1,036 18-23 12.9 1,036 5.7 973 24-35 15.7 1,899 5.6 1,816 36-47 16.1 1,916 6.3 1,774 48-59 17.9 1,921 6.9 1,756 Sex Male 15.2 4,450 5.6 4,172 Female 13.7 4,397 5.6 4,091 Mother’s interview status Interviewed 13.9 7,672 5.3 7,164 Not interviewed but in household 21.2 189 8.2 181 Not interviewed, and not in the household1 17.3 986 7.3 918 Residence Urban 3.9 2,215 2.4 2,126 Rural 18.0 6,632 6.7 6,137 Tanzania Mainland/ Zanzibar Mainland 14.8 8,611 5.7 8,066 Urban 4.1 2,149 2.4 2,077 Rural 18.4 6,462 6.8 5,989 Zanzibar 0.0 236 0.7 197 Unguja 0.0 151 0.5 129 Pemba 0.0 85 1.1 68 Zone Western 27.7 1,100 9.3 1,024 Northern 1.4 827 1.4 782 Central 1.7 979 1.4 935 Southern Highlands 10.4 476 2.0 462 Southern 18.8 359 8.2 347 South West Highlands 3.1 847 2.8 737 Lake 23.5 2,909 8.9 2,676 Eastern 10.6 1,115 4.0 1,102 Zanzibar 0.0 236 0.7 197 Region Dodoma 0.0 373 0.5 349 Arusha 0.0 291 0.0 280 Kilimanjaro 0.0 166 0.5 159 Tanga 3.2 370 3.1 343 Morogoro 23.1 365 9.1 354 Pwani 15.3 183 5.8 172 Dar es Salaam 1.1 568 0.3 575 Lindi 17.4 165 9.3 162 Mtwara 20.0 194 7.3 185 Ruvuma 22.6 213 4.4 212 Iringa 0.5 151 0.0 145 Mbeya 0.7 490 2.4 404 Singida 5.5 309 3.0 306 Tabora 19.5 616 7.0 584 Rukwa 2.7 237 1.4 220 Kigoma 38.1 484 12.3 441 Shinyanga 16.5 404 4.3 372 Kagera 41.0 508 11.6 483 Mwanza 15.3 689 8.4 603 Mara 19.1 440 5.1 401 Manyara 0.0 297 0.8 281 Njombe 0.4 112 0.0 106 Katavi 13.5 120 6.5 113 Simiyu 13.4 460 6.0 436 Geita 38.4 407 17.7 382 Kaskazini Unguja 0.0 38 0.0 36 Kusini Unguja 0.3 25 1.5 24 Mjini Magharibi 0.0 88 0.4 70 Kaskazini Pemba 0.0 44 1.0 31 Kusini Pemba 0.0 40 1.2 37 (Continued…) 3 2 1 Reading and Understanding Tables from the 2015 TDHS-MIS • xxvii Table 12.16—Continued Malaria prevalence using a RDT Malaria prevalence using microscopy Background characteristic Tested positive Number of children tested Tested positive Number of children tested Mother’s education2 No education 21.0 1,726 8.8 1,610 Primary incomplete 23.3 1,030 7.3 956 Primary complete 11.6 4,028 4.5 3,761 Secondary+ 3.5 1,066 1.3 1,008 Wealth quintile Lowest 22.3 2,158 8.2 2,006 Second 21.9 1,966 8.3 1,823 Middle 14.8 1,727 6.2 1,599 Fourth 6.0 1,599 2.0 1,496 Highest 1.0 1,398 1.0 1,339 Total 14.4 8,847 5.6 8,263 Step 1: Read the title and subtitle. In this case, the table presents malaria prevalence among children age 6- 59 months according to both a rapid diagnostic test (RDT) and microscopy. Step 2: Identify the information presented in the table— highlighted in green in the table on the left and above. In this table there is only one indicator—malaria prevalence, but it is divided into two categories. The first two columns show malaria prevalence according to RDT. The last two columns show malaria prevalence according to microscopy. Step 3: Look at the row headings to identify the background characteristics. In this table, malaria prevalence is presented by age, sex, mother’s interview status, urban and rural residence, Tanzania Mainland/Zanzibar, zone, region, mother’s education level, and wealth quintile. Step 4: Look at the rows at the bottom of the table to determine the total proportion of children with malaria according to RDT. This shows that 14.4% of children age 6-59 months in Tanzania tested positive for malaria by RDT. Step 5: In Tanzania, 14.4% of children age 6-59 months tested positive for malaria by RDT, but a closer look at the table shows how malaria prevalence varies throughout Tanzania. To gain a better understanding of differences in the prevalence of malaria according to RDT, consider the following questions: Practice:  Is malaria prevalence more common in urban or rural areas? Malaria prevalence is more common in rural areas (18.0%) than in urban areas (3.9%).  Now, compare malaria prevalence among girls and boys. Malaria prevalence is slightly higher among boys than girls (15.2% versus 13.7%). However, the difference between these two groups is small.  What are the lowest and the highest percentages (range) of malaria prevalence by zone? Malaria prevalence ranges from a low of 0.0% in Zanzibar to a high of 27.7% in Western zone.  Look for patterns: Does malaria prevalence by RDT vary by background characteristics? For example, is there a clear pattern of malaria prevalence by age in months? By mother’s education? By wealth quintile? Answers: Malaria prevalence is highest among children age 48-59 months (17.9%) and lowest among children age 6-8 and 9-11 months (8.4% each). Malaria prevalence generally decreases as mother’s education increases; 21.0% of children whose mothers have no education tested positive for malaria by RDT, compared to 3.5% of children whose mothers have secondary or higher education. Finally, there is a pattern in malaria prevalence by household wealth quintile. Malaria prevalence decreases as household wealth increases; 22.3% of children living in households in the lowest wealth quintile tested positive for malaria by RDT, compared to just 1.0% of children living in households in the highest wealth quintile. By looking at patterns by background characteristics, we can see which groups are more in need of interventions to address malaria. Resources are often limited; looking for patterns can help programme planners and policymakers determine how to most effectively use resources. 4 xxviii • Reading and Understanding Tables from the 2015 TDHS-MIS Example 3: Prevalence and Treatment of Symptoms of ARI A Question Asked of a Subgroup of Survey Respondents Table 10.5 Prevalence and treatment of symptoms of ARI Among children under age 5, the percentage who had symptoms of acute respiratory infection (ARI) in the 2 weeks before the survey and among children with symptoms of ARI, the percentage for whom advice or treatment was sought from a health facility or provider, and the percentage who received antibiotics as treatment, according to background characteristics, Tanzania DHS-MIS 2015-16 Among children under age 5: Among children under age 5 with symptoms of ARI: Background characteristic Percentage with symptoms of ARI1 Number of children Percentage for whom advice or treatment was sought from a health facility or provider2 Percentage for whom treatment was sought same or next day Percentage who received antibiotics Number of children Age in months <6 4.1 1,012 (63.8) (39.0) (19.2) 41 6-11 5.3 999 (68.4) (42.5) (55.3) 53 12-23 5.2 2,134 59.1 42.1 37.4 111 24-35 3.9 1,817 47.2 44.9 45.8 70 36-47 2.1 1,791 (55.2) (24.7) (33.3) 37 48-59 2.5 1,768 (36.0) (32.2) (39.8) 44 Sex Male 3.8 4,806 52.4 36.9 36.8 183 Female 3.7 4,714 58.7 42.0 42.3 174 Residence Urban 5.1 2,541 64.4 47.2 41.2 129 Rural 3.3 6,980 50.4 34.9 38.5 228 Tanzania Mainland/ Zanzibar Mainland 3.7 9,268 54.7 38.9 39.1 346 Urban 5.1 2,475 63.7 46.5 40.6 126 Rural 3.2 6,794 49.6 34.5 38.2 220 Zanzibar 4.3 252 78.6 53.0 52.7 11 Unguja 4.0 158 (79.9) (56.6) (43.0) 6 Pemba 4.9 94 (76.9) (48.1) (66.0) 5 Zone Western 3.2 1,170 (38.6) (37.3) (37.7) 37 Northern 3.6 901 (72.8) (23.6) (60.2) 32 Central 2.0 1,065 * * * 21 Southern Highlands 2.6 517 * * * 14 Southern 2.5 372 * * * 9 South West Highlands 4.3 914 (39.1) (27.3) (17.0) 40 Lake 4.3 3,014 50.0 39.1 32.9 130 Eastern 4.8 1,315 (75.0) (51.7) (50.3) 63 Zanzibar 4.3 252 78.6 53.0 52.7 11 Education No education 3.7 2,013 44.8 20.7 35.8 74 Primary incomplete 5.0 1,241 49.9 31.5 40.8 62 Primary complete 3.2 4,901 60.1 45.1 42.0 159 Secondary+ 4.5 1,365 61.8 54.8 36.1 61 Wealth quintile Lowest 2.9 2,321 37.0 27.8 40.6 66 Second 3.1 2,014 48.7 34.2 29.2 63 Middle 3.4 1,838 47.7 36.8 39.9 62 Fourth 4.8 1,773 62.0 44.2 38.4 85 Highest 5.1 1,575 74.9 49.7 47.4 81 Total 3.7 9,520 55.4 39.3 39.5 357 Note: Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. 1 Symptoms of ARI (cough accompanied by short, rapid breathing which was chest-related, and/or by difficult breathing which was chest-related) is considered a proxy for pneumonia. 2 Excludes pharmacy, shop, and traditional practitioner. 3 Includes grass, shrubs, and crop residues. b a 4 1 3 2 3 Reading and Understanding Tables from the 2015 TDHS-MIS • xxix Step 1: Read the title and subtitle. In this case, the table is about two separate groups of children: all children under 5 (a) and children under five who had symptoms of acute respiratory infection (ARI) in the two weeks before the survey (b). Step 2: Identify the two panels. First identify the columns that refer to all children under five (a), and then isolate the columns that refer only to those children under five who had symptoms of ARI in the two weeks before the survey (b). Step 3: Look at the first panel. What percentage of children under five had symptoms of ARI in the two weeks before the survey? It’s 3.7%. Now look at the second panel. How many children under five are there who had symptoms of ARI in the two weeks before the survey? It’s 357 children or 3.7% of the 9,520 children under five (with rounding). The second panel is a subset of the first panel. Step 4: Only 3.7% of children under five had symptoms of ARI in the two weeks before the survey. Once these children are further divided into the background characteristic categories, there may be too few cases for the percentages to be reliable.  What percentage of children under five in Western zone who had symptoms of ARI in the two weeks before the survey received antibiotics? 37.7%. This percentage is in parentheses because there are fewer than 50 children (unweighted) in this category. Readers should use this number with caution—it may not be accurate. (For more information on weighted and unweighted numbers, see Example 4.)  What percentage of children under five in Central zone had symptoms of ARI in the two weeks before the survey received antibiotics? There is no number in this cell—only an asterisk. This is because fewer than 25 children in Central zone (unweighted) had symptoms of ARI in the two weeks before the survey. Results for this group are not reported. The subgroup is too small, and therefore the data are not reliable. Note: When parentheses or asterisks are used in a table, the explanation will be noted under the table. If there are no parentheses or asterisks on a table, you can proceed with confidence that enough cases were included in all categories that the data are reliable. xxx • Reading and Understanding Tables from the 2015 TDHS-MIS Example 4: Understanding Sampling Weights in TDHS-MIS Tables A sample is a group of people who have been selected for a survey. In DHS-MIS surveys, the sample is designed to represent the national population of age 15-49. Most countries also want to collect and report data on smaller geographical areas. However, doing so requires a minimum sample size per area. For the 2015- 16 TDHS-MIS, the survey sample is representative of the country as a whole, residence, Tanzania Mainland and Zanzibar, nine geographic zones, and 30 regions. To generate statistics that are representative of Tanzania and the 30 regions, the number of women surveyed in each region should contribute to the size of the total (national) sample in proportion to size of the region. However, if some regions have small populations, then a sample allocated in proportion to each region’s population may not include sufficient women from each region for analysis. To solve this problem, regions with small populations are oversampled. Let’s say that you have enough money to interview 13,266 women and want to produce results that are representative of Tanzania and its regions (as in Table 3.1). However, the total population of Tanzania is not evenly distributed among the regions: some regions, such as Dar es Salaam, are heavily populated while others, such as Kusini Unguja are not. Thus, Kusini Unguja must be oversampled. A sampling statistician determines how many women should be interviewed in each region in order to get reliable statistics. The blue column (1) in the table above shows the actual number of women interviewed in each region. Within the regions, the number of women interviewed ranges from 333 in Pwani to 797 in Dar es Salaam. The number of interviews is sufficient to get reliable results in each region. With this distribution of interviews, some regions are overrepresented and some regions are underrepresented. For example, the population in the Kusini Unguja region is less than 1% of the population in Tanzania, while Dar es Salaam is about 12% of the population in Tanzania. But as the blue column shows, the number of women interviewed in Kusini Unguja accounts for 3% of the total sample of women interviewed (361/13,266) and the number of women interviewed in Dar es Salaam accounts for 6% of the total sample of women interviewed (797/13,266). This unweighted distribution of Tanzanian women does not accurately represent the population. In order to get statistics that are representative of Tanzania, the distribution of the women in the sample needs to be weighted (or mathematically adjusted) such that it resembles the true distribution in the country. Women from a small region, like Kusini Unguja, should contribute a small amount to the national total. Women from a large region, like Dar es Salaam should contribute much more. Therefore, DHS statisticians mathematically calculate a “weight” which is used to adjust the number of women from each region so that each region’s contribution to the total is proportional to the actual population of the region. The numbers in the purple column (2) represent the “weighted” values. The weighted values can be smaller or larger than the unweighted values at the regional level. The total national sample size of 13,266 women has not changed after weighting, but the distribution of the women in the regions has changed to represent their contribution to the total population size. Table 3.1 Background characteristics of respondents Percent distribution of women and men age 15-49 by selected background characteristics, Tanzania DHS-MIS 2015-16 Women Background characteristic Weighted percent Weighted number Unweighted number Region Dodoma 4.3 572 343 Arusha 3.8 508 420 Kilimanjaro 2.7 361 370 Tanga 5.3 706 465 Morogoro 4.8 636 345 Pwani 2.1 285 333 Dar es Salaam 11.6 1,536 797 Lindi 2.2 288 380 Mtwara 3.1 412 348 Ruvuma 2.7 360 383 Iringa 1.8 245 340 Mbeya 6.2 828 374 Singida 2.8 370 413 Tabora 5.6 737 560 Rukwa 2.2 288 425 Kigoma 4.1 542 491 Shinyanga 3.8 504 516 Kagera 4.6 612 416 Mwanza 6.5 859 496 Mara 3.9 523 531 Manyara 3.0 394 434 Njombe 1.5 203 359 Katavi 1.0 130 466 Simiyu 3.6 479 587 Geita 3.7 485 535 Kaskazini Unguja 0.4 56 366 Kusini Unguja 0.3 35 361 Mjini Magharibi 1.5 201 708 Kaskazini Pemba 0.4 56 338 Kusini Pemba 0.4 55 366 Total 15-49 100.0 13,266 13,266 3 2 1 Reading and Understanding Tables from the 2015 TDHS-MIS • xxxi How do statisticians weight each category? They take into account the probability that a woman was selected in the sample. If you were to compare the red column (3) to the actual population distribution of Tanzania, you would see that women in each region are contributing to the total sample with the same weight that they contribute to the population of Tanzania. The weighted number of women in the survey now accurately represents the proportion of women who live in Kusini Unguja and the proportion of women who live in Dar es Salaam. With sampling and weighting, it is possible to interview enough women to provide reliable statistics at national and regional levels. In general, only the weighted numbers are shown in each of the TDHS-MIS tables, so don’t be surprised if these numbers seem low: they may actually represent a larger number of women interviewed. Acronyms and Abbreviations • xxxiii ACRONYMS AND ABBREVIATIONS ACT artemisinin combination therapy AD age at death ADDO accredited drug dispensing outlet AIDS acquired immunodeficiency syndrome ARI acute respiratory infection BCC behavioural change communication BCG bacillus Calmette-Guerin BEmONC basic emergency obstetric and neonatal care BMI body mass index BOT Bank of Tanzania BRN Big Result Now CEmONC comprehensive emergency obstetric and neonatal care CHMT Council Health Management Team CHW Community Health Worker DFATD Canadian Department of Foreign Affairs, Trade and Development DP development partner EA enumeration area FGM female genital mutilation FyPD 5-year development plan GAR gross attendance ratio GDP gross domestic product GFR general fertility rate GPI gender parity index HFS health financing strategy HIV human immunodeficiency virus HRH human resource for health HSS health system strengthening HSSP health sector strategic plan ICD-10 International Classification of Diseases, Tenth Revision IEC Information, Education, and Communication IEC/BCC Information, Education and Communication/Behaviour Change Communication IHI Ifakara Health Institute IPTp intermittent preventive treatment for pregnant women IT information technology ITN insecticide-treated net IYCF infant and young child feeding IUD intrauterine device KIO3 potassium iodate LGA local government authority xxxiv • Acronyms and Abbreviations MAD minimum acceptable diet MDA ministry, department and agency MDG millennium development goal MDU Ministerial Delivery Unit MMAM Mpango wa Maendeleo ya Afya ya Msingi MMRate maternal mortality rate MMRatio maternal mortality ratio MoHCDGEM Ministry of Health, Community Development, Gender, Elderly and Children mRDT malaria rapid diagnostic test MSD Medical Stores Department NAR net attendance ratio NBS National Bureau of Statistics NCD noncommunicable disease NEHCIP National Essential Health Care Intervention Package NGO nongovernmental organisation NKRA National Key Result Area NMCP National Malaria Control Programme NNS National Nutritional Strategy OCGS Office of Chief Government Statistician ORS oral rehydration solution ORT oral rehydration therapy PDB Presidential Delivery Bureau Pf Plasmodium falciparum PHC Population and Housing Census PHCSDP Primary Health Care Service Development Programme PMO-RALG Prime Minister’s Office, Regional Administration and Local Governments PPM parts per million RDT rapid diagnostic test RHF recommended home fluid RHMT Regional Health Management Team RMNCAH Reproductive, Maternal, Neonatal, Child and Adolescent Health RS regional secretary SD standard deviations SDG sustainable development goal SEZ special economic zone SMS short message service SNHI single national health insurer TDHS-MIS Tanzania Demographic and Health Survey and Malaria Indicators Survey TFNC Tanzania Food and Nutrition Centre UIC urinary iodine concentration UNFPA United Nations Population Fund UNICEF United Nations Children’s Fund USAID United States Agency for International Development VAD vitamin A deficiency WHO World Health Organization YSD years since death ZAMEP Zanzibar Malaria Elimination Programme xxxvi • Map of Tanzania Introduction and Survey Methodology • 1 INTRODUCTION AND SURVEY METHODOLOGY 1 1.1 GEOGRAPHY, HISTORY, AND THE ECONOMY 1.1.1 Geography he United Republic of Tanzania is the largest country in East Africa, covering 940,000 square kilometres, 60,000 of which are inland water. Tanzania lies south of the equator and shares borders with eight countries: Kenya and Uganda to the North; Rwanda, Burundi, the Democratic Republic of Congo, and Zambia to the West; and Malawi and Mozambique to the South. Tanzania has an abundance of inland water, with several lakes and rivers. Lake Tanganyika runs along the western border and is Africa’s deepest and longest freshwater lake and the world’s second deepest lake. Lake Victoria, the world’s second largest lake, drains into the Nile River, which flows into the Mediterranean Sea. The Rufiji River is Tanzania’s largest river, and it drains into the Indian Ocean, south of Dar es Salaam. Although there are many rivers, only the Rufiji and the Kagera rivers, which empty into Lake Victoria, are navigable by anything larger than a canoe. One of Tanzania’s most distinctive geological features is the Great Rift Valley, which was caused by geological faulting throughout Eastern Africa and is associated with volcanic activity in the north-eastern regions of the country. Two branches of the Great Rift Valley run through Tanzania. The western branch holds Lakes Tanganyika, Rukwa, and Nyasa, while the Eastern branch, which ends in northern Tanzania, includes Lakes Natron, Manyara, and Eyasi. Except for a narrow belt of 900 square kilometres along the coast, most of Tanzania lies 200 metres or more above sea level, and much of the country is above 1,000 metres. In the North, Mount Kilimanjaro rises to 5,895 metres—the highest point in Africa. The main climatic feature for most of the country is a long dry spell from May to October, followed by a period of rainfall between November and May. The main rainy season is from March to May, along the coast and around Mount Kilimanjaro, with short periods of rain between October and December. In the western part of the country, around Lake Victoria, the rainfall is well distributed throughout the year, with the peak period falling between March and May. 1.1.2 History Tanzania (formerly Tanganyika) became independent of British colonial rule on 9 December 1961. One year later, on 9 December 1962, it became a republic, severing all links with the British crown except for its membership in the Commonwealth. The offshore island of Zanzibar became independent on 12 January 1964, after the overthrow of the rule of the sultanate. On 26 April 1964, Tanganyika and Zanzibar joined to form the United Republic of Tanzania. Tanzania is currently operating under a multiparty democratic system of government, with the president and the national assembly members elected every 5 years. Tanzania’s president can hold office for a maximum of two 5-year terms. For administrative purposes, Tanzania Mainland is divided into 25 regions, and Zanzibar is divided into 5 regions. Each region is subdivided into several districts. 1.1.3 Economy Tanzania has a mixed economy. Agriculture, comprising crop growth, animal husbandry, forestry, fishery, and hunting, played a key role in past years. In the current economy, activities in the service industry T 2 • Introduction and Survey Methodology account for 52% of the gross domestic product (GDP). In 2015 the agricultural sector growth declined to 2.3% compared with growth of 3.4% in 2014 (National Bureau of Statistics 2015). During the same period, the growth rate of crops decreased from 4.0% to 3.2% and that of livestock increased from 2.2% in 2014 to 2.4% in 2015. The decrease in agricultural crop production was attributed to unreliable and untimely rainfall. The agricultural sector faces challenges, including low productivity, dependence on rainfall, backward technology, use of hand hoe, and a lack of both stable markets and agro processing industries. The increase in the growth rate of livestock production was due to improved pasture land, increased extension services for livestock development, and an increase in value of livestock and livestock products. In 2015, the GDP grew by 7.0%, as was the case in 2014. The 2015 GDP at current prices was TZS 90,863 billion, which is equivalent to TZS 44,101 billion at 2007 constant prices. With an estimated population of 47.4 million on the Tanzania Mainland in 2015, the per capita income was TZS 1,918,928 at current prices, compared with TZS 1,730,405 in 2014, indicating an increase of 10.9% (National Bureau of Statistics 2015). 1.2 POPULATION Tanzania has undertaken five population and housing censuses since its independence in 1961. The first census, conducted in 1967, reported a total population of 12.3 million. According to the 2012 census, the population had increased to 44.9 million (Table 1.1). The 2016 projected population is 50.1 million (NBS 2016). Although the population of Tanzania has increased four times its earlier size in the past four decades, the country is still sparsely populated. Despite the dispersed population, density is high in some parts of the country and has been increasing over time. In 1967, the average population density was 14 persons per square kilometre; by 2012, it had increased to 51 persons per square kilometre. The high population growth rate in Tanzania has been brought about by high fertility and declining mortality levels. According to the 2012 census, the life expectancy at birth is 62 years. The population of Tanzania has continued to be predominantly rural despite the increase in the proportion of urban residents over time, from 6% in 1967 to 30% in 2012. 1.3 POPULATION AND HEALTH POLICIES AND PROGRAMMES 1.3.1 National Population Policy The government of the United Republic of Tanzania adopted the National Population Policy in 1992. Since then, developments have taken place, both nationally and internationally, that have a direct bearing on population and development. The Government revised the National Population Policy in 2006 to accommodate these developments (Ministry of Planning, Economy and Empowerment 2006). The key objectives of the revised policy are to provide a framework and guidelines for integration of population variables in the development process. Specific issues addressed in the guidelines include (1) determining priorities in population and development programmes, (2) strengthening the preparation and implementation of socioeconomic development planning, and (3) coordinating and influencing other policies, strategies, and programmes that ensure sustainable development. Guidelines for promoting gender equality and the empowerment of women are also included (Ministry of Planning, Economy, and Empowerment 2009). Goals of the Policy The overriding concern of the revised 2006 National Population Policy has been to improve the standard of living and quality of life of the country’s population. The main goal of the policy is to direct development of other policies, strategies, and programmes that ensure sustainable development of the people. Introduction and Survey Methodology • 3 Specific goals of this policy focus on:  Attainment of gender equity, equality, women’s empowerment, social justice, and development for all  Sustainable development and eradication of poverty  Harmonious interrelationships among population, resource utilisation, and the environment  Increased and improved availability and accessibility of quality social services 1.3.2 Vision 2025 The Arusha Declaration of 1967 was the first vision document of the country after independence. The Vision 2025 (formulated in 1998) is an update of that declaration. Tanzania Vision 2025 provides direction and a philosophy for long-term development. Tanzania wants to achieve by 2025 a high quality of livelihood for its citizens; peace, stability, and unity; good governance; a well-educated society; and a competitive economy capable of producing sustainable growth and shared benefits. The document identifies health as one of the priority sectors contributing to a higher quality of livelihood for all Tanzanians. This is expected to be attained through strategies that will achieve the following health service goals:  Access to quality primary health care for all  Access to quality reproductive health service for all individuals of appropriate ages  Reduction in infant and maternal mortality rates to three-quarters of 1998 levels  Universal access to clean and safe water  Life expectancy comparable to the level attained by typical middle-income countries  Food self-sufficiency and food security  Gender equality and empowerment of women in all health parameters 1.3.3 The National Strategy got Growth and Reduction of Poverty (NSGRP) The National Strategy for Growth and Reduction of Poverty (NSGRP), known in Kiswahili as the MKUKUTA, represented Tanzania’s commitment to the achievement of the Millennium Development Goals (MDGs). MKUKUTA II covered the period 2010/11–2014/15. It focused on growth, social well- being, and governance, and was a framework for all government development efforts and for mobilising resources. The MKUKUTA aimed to foster greater collaboration among all sectors and stakeholders. It mainstreamed crosscutting issues (gender, environment, HIV/AIDS, human rights, disability, children, youth, elderly, employment, and settlements) into all sector strategies. All sectors were involved in a collaborative effort rather than segmented into separate activities. 1.3.4 The 5-Year Development Plan (FYDP I) 2011/12–2015/16 The 5-Year Development Plan (FYDP I) 2011/12–2015/16 aimed to mobilise Tanzania’s resource potential in order to fast-track provision of the basic conditions for broad-based and pro-poor growth. Five crucial elements were to generate this growth momentum: 1. Large investments in energy and transport infrastructure 2. Strategic investments to expand productive sectors (growing high-value crops and producing food for self-sufficiency and export; tapping large natural gas and phosphate deposits; developing Special Economic Zones (SEZs) to foster economic growth) 3. Skills development 4. Improved business environment 5. Institutional reforms for effective implementation, monitoring, and evaluation of the plan 4 • Introduction and Survey Methodology The FYDP I set the following goals for the health sector:  Increase accessibility to health services, based on equity and gender balance.  Improve quality of health services.  Strengthen management of the health system.  Strengthen management of policies and regulation of health services.  Enhance human resource development for health and social welfare. 1.3.5 Big Results Now Initiative As part of the Tanzanian Government’s effort to transform the country from a low-income to a middle- income economy, Tanzania is set to adopt the Malaysian Model of Development—The Big Results Now (BRN) initiative—in its own development outlook, which was to be implemented at the beginning of the 2013/2014 financial year. In 2014, the National Key Result Area (NKRA) in health care was introduced in the Big Results Now approach, to join other key result areas adopted by the Government of Tanzania (GOT) in 2013. The goal was to enhance the implementation of the 5-Year Development Plan 2011/12–2015/16 and Vision 2025. The health care NKRA is the eighth area under the Big Results Now programme. The BRN approach or methodology emphasises priority setting, focused planning, and efficient resource management. The BRN approach aims to instil a sense of accountability and discipline in implementation through focused monitoring and evaluation. The Presidential Delivery Bureau manages and directs the implementation of the NKRAs and monitors the performance of the outcomes. It also supports the Ministerial Delivery Units (MDUs) at ministerial level to implement and monitor priority initiatives. The BRN has identified priority regions for actions, based on a thorough situation analysis. Most underserved or underperforming regions will be targeted first. BRN activities constitute the core of Health Sector Strategic Plan (HSSP) IV and are fully integrated. The 22 initiatives listed in the health care NKRA will continue beyond June 2018. Similar achievements planned for BRN target regions will be achieved or surpassed countrywide by the end of the HSSP IV period. 1.3.6 Health Policy The Health Policy 2007 outlines achievements and challenges facing the health sector. The vision of this policy is to have a healthy society, with improved social wellbeing that will contribute effectively to personal and national development. The mission is to provide basic health services in accordance with geographical conditions, which are of acceptable standards, affordable, and sustainable. The policy prioritises the provision of health services to those most at risk and satisfies the needs of citizens in order to increase the lifespan of all Tanzanians. Specifically the Government targets:  Reducing morbidity and mortality to increase the lifespan of all Tanzanians by providing quality health care  Ensuring that basic health services are available and accessible  Preventing and controlling communicable and non-communicable diseases  Sensitising the citizens to preventable diseases  Creating awareness in individual citizens of responsibility for personal health and health of their family Introduction and Survey Methodology • 5  Improving partnership among the public sector, private sector, religious institutions, civil society, and community in provision of health services  Planning, training, and increasing the number of competent health staff  Identifying and maintaining the infrastructures and medical equipment  Reviewing and evaluating the health policy of 2007 and guidelines, laws, and standards for provision of health services The document looks at health policies and statements in the following areas:  Preventive services: Control disease incidences and disability  Epidemics: Control communicable diseases, especially diseases from outside  Non-communicable diseases: Promote healthier lifestyles and adequate treatment  Maternal and child health: Reduce maternal and child mortality in line with MDGs  Reproductive health: Make services available, especially for youth and men  Primary Health Care (PHC): Make PHC accessible for all citizens  Health education and advocacy: Get across the message that every individual can improve his or her health status  Environmental Health: Promote a sustainable healthy environment for the whole community  Occupational health: Protect and improve workers’ health status  Curative care: Deliver safe health care services to the community  Medicines and supplies: Ensure quality and availability of sufficient medicines and supplies  Safe blood transfusions: Make safe blood available throughout the country  Mental health: Promote mental health in the community and prevent illnesses  Traditional medicine and traditional midwives: Increase coordination and partnerships  Cells and genome: Develop proper use of technology of genetic engineering  Control of food, medicines, other: Ensure foods are safe and meet defined standards  Diagnosis of diseases: Provide accurate diagnosis and forensic investigations  Quality improvement and standards: Attain at least minimum standards  Coordination in health sector: Participatory, transparent, and sustainable system for all stakeholders  Human resources development: Provide sufficient staff with required skills mix 1.3.7 Primary Health Care Service Development Programme (2007-2017) In 2007 the Ministry of Health, Community Development, Gender, Elderly and Children (MoHCDGEC) developed the Primary Health Care Service Development Programme, better known in Kiswahili as Mpango wa Maendeleo ya Afya ya Msingi (MMAM) 2007-2017. The objective of the MMAM 6 • Introduction and Survey Methodology programme was to accelerate the provision of primary health care services for all by 2012, while the remaining 5 years of the programme were to focus on consolidation of achievements. Major areas were strengthening health systems, rehabilitation, human resource development, strengthening the referral system, health sector financing, and provision of medicines, equipment, and supplies. This programme is being implemented by the MoHCDGEC in collaboration with other sectors in the existing government administration. These sectors include the Prime Minister’s office, regional administration and local government (PMO-RALG), regional secretariats (RSs), local government authorities (LGAs), and village committees. The first element was to increase the health workforce by increasing the throughput in the existing training institutions by 100%, upgrading four schools to enrol nurses, producing health tutors, and upgrading the skills of existing staff by provision of information technology skills and acquiring new medical technology. The rehabilitation of existing health facilities and construction of new ones, to have a dispensary in each village and a health centre in each ward, was planned, as was improving the outreach services. The referral system was to be strengthened by improving information communication systems and transport. The Programme was also designed to address the revised health policy and the health- related MDGs in the areas of maternal health, child health, and priority diseases. 1.3.8 Health Sector Strategic Plan III (2009-2015) The Health Sector Strategic Plan III (HSSP III) was a crosscutting strategic plan for the health sector of Tanzania for the period July 2009 - June 2015. It provided an overview of the priority strategic directions across the sectors guided by Vision 2025, the National Programme for Economic Growth and Poverty Reduction (MKUKUTA in Kiswahili) and the MDGs, and the National Health Policy. It served as the guiding document for development of council and hospital strategic plans and for annual work plans. The formulation process of the HSSP III was led by the Health Sector Reform Secretariat under the Division of Policy and Planning, MoHCDGEC. The process involved key stakeholders from ministries, departments, and agencies. The private sector and development partners also participated in HSSP III preparation. 1.3.9 The National Road Map Strategic Plan to Accelerate Reduction of Maternal, Newborn, and Child Deaths in Tanzania-One Plan (2008-2015) The main goal of this strategic plan was to reduce maternal, neonatal, and child morbidity and mortality and to attain MDG 4 (to reduce child mortality by two-thirds from the rate in 1990) and 5 (to reduce maternal mortality by three-quarters from the rate in 1990). The target date for achievement of these goals was December 2015. Broad objectives:  To provide skilled attendance to women during pregnancy, childbirth, postnatal and neonatal periods, and children at all levels of the health care delivery system  To strengthen the capacity of individuals, families, communities, and organisations to improve maternal, newborn, and child health Operational targets that were to have been achieved by the end of 2015:  To reduce maternal mortality from 578 to 193 deaths per 100,000 live births  To reduce neonatal mortality from 32 to 19 deaths per 1,000 live births  To reduce under-5 mortality from 112 to 54 deaths per 1,000 live births  To increase coverage of emergency obstetric care from 64% to 100% of hospitals and basic comprehensive emergency obstetric care services from 5% to 70% of health centres and dispensaries Introduction and Survey Methodology • 7  To increase modern contraceptive prevalence among women age 15-49 from 20% to 60%  To increase provision of services that will prevent HIV transmission from mother to child in at least 80% of pregnant women, their babies, and their families  To increase the proportion of health facilities offering essential newborn care to 75%  To reduce the prevalence of stunting among children under age 5 from 38% to 22% and to reduce the prevalence of underweight among children under age 5 from 22% to 14%  To increase coverage of children under age 5 sleeping under ITNs from 47% to 80%  To increase the number of health facilities providing adolescent-friendly reproductive health services from 10% to 80%  To increase immunization coverage of DTP-HB3 and measles vaccine to above 90% in 90% of the districts To achieve the targets set for 2015, the following strategies were launched:  Advocacy and resource mobilization  Health system strengthening and capacity development  Community mobilization  Promotion of reproductive and child health behavioural change  Fostering of partnership and coordination The MoHCDGEC was to mobilise resources and advocate for the reduction of maternal, newborn, and child deaths. The MoHCDGEC was also responsible for the overall technical leadership, guidance, and coordination of the implementation and monitoring of the strategic plan. The goal was to accelerate the reduction of maternal, newborn, and child deaths and thereby achieve the relevant MDGs. 1.3.10 The Sharpened One Plan to Accelerate Progress (2014-2015) The Sharpened One Plan 2014–2015 aimed to accelerate implementation of the interventions and strategies stipulated in “The National Road Map Strategic Plan to Accelerate Reduction of Maternal, Newborn, and Child Deaths in Tanzania 2008-2015 (One Plan)” in an integrated manner that addressed the continuum of care. The rationale for taking the integrated approach relies on a number of factors:  Specific interventions delivered in a specific time frame have multiple benefits.  Linking interventions in packages can reduce costs; facilitate greater efficiency in training, monitoring, and supervision; and strengthen supply systems.  Integration of services increases uptake and promotes continuation of positive behaviours.  Integration maximises programme achievements. The Sharpened One Plan adopted the goal and objectives of the One Plan. The focus of the Sharpened One Plan for the remaining 600 days of the One Plan (June 2014 to December 2015) was refined based on the One Plan mid-term review findings in line with five strategic areas as defined by A Promise Renewed initiative. Strategic Area 1: Geographic focus with increased efforts in Lake zone (Kagera, Mwanza, Geita, Mara, Simiyu, and Shinyanga regions) and Western zones (Tabora and Kigoma regions) where maternal, newborn, and child mortality is highest, with a focus on reducing rural-urban disparities 8 • Introduction and Survey Methodology Strategic Area 2: High burden, population focusing, health systems to scale up access for underserved women, adolescents, and children; maintain gains in maternal and child health; scale-up interventions particularly in rural or marginally performing areas Strategic Area 3: High impact interventions that target and expand coverage of selected evidence-based interventions that will have the greatest impact on lives saved, specifically in family planning, care at birth, and postpartum/ postnatal care Strategic Area 4: Education, empowerment, equality to collaborate and coordinate with supportive policies and legal environment that influence the social determinants of health and information, education and communication/behavioural change communication Strategic Area 5: Mutual accountability and transparency to strengthen all levels of the health systems; and invest in a Health Management Information System (HMIS) to capture data, monitor, and evaluate progress using the Reproductive and Maternal Newborn and Child Health (RMNCH) scorecard 1.3.11 National Nutrition Strategy The Government of Tanzania developed the National Nutrition Strategy (NNS) to put forward the priorities for July 2011 to June 2016. This strategy aims to ensure that the nation and its people are properly nourished. The strategy is in-line with, and will contribute to, the National Development Vision 2025, MKUKUTA, the African Regional Nutrition Strategy (2005-2015), and the policies and strategies of the Government of Tanzania. The goal of the strategy is that all Tanzanians attain adequate nutritional status, which is an essential requirement for a healthy and productive nation. This goal will be achieved through policies, strategies, programmes, and partnerships that deliver evidence-based and cost-effective interventions to improve nutrition. The targets to be achieved by 2015 were as follows:  Reduce the prevalence of underweight in children age 0-59 months (weight-for-age z-score <-2 SD) from 16% in 2010 to 11%.  Reduce the prevalence of stunting in children age 0-59 months (height-for-age z- score <-2 SD) from 42% in 2010 to 27%.  Increase prevalence of exclusive breastfeeding in children <6 months from 50% (2010) to 60%.  Sustain the prevalence of wasting in children age 0-59 months (weight-for-height z- score <-2 SD) below 5% at all times1,2.  Sustain the prevalence of thinness (body mass index <18.5 kg/m2) among women of reproductive age below the 2005 prevalence of 10% at all times.  Reduce the prevalence of vitamin A deficiency among children age 6-59 months (serum retinol levels <20 pg/dL) from 24% in 1997 to <15%.  Reduce the prevalence of anaemia (haemoglobin concentration <11 g/dl) among pregnant women from 48.4% in 2004/5 to 35%. 1 Note: Prevalence rate according to New WHO Child Growth Standards 2 The 5% target is less that the 2% target set in the NSGRP, as it is felt that the latter target is too ambitious. Introduction and Survey Methodology • 9  Reduce the prevalence of anaemia among children age 6-59 months (haemoglobin concentration <11 g/dl) from 71.8% in 2004/5 to 55%.  Maintain the prevalence of iodine deficiency among children age 6-12 (urinary iodine concentrations <100 pg/d) at <50%. Behaviour change and service provision objectives:  Increase the proportion of infants age less than 6 months who are exclusively breastfed from 41% to 60%.  Increase the proportion of infants age 4-5 months who are exclusively breastfed from 13.5% to 25%.  Maintain the proportion of infants age 6-9 months who are fed solid foods in addition to breast milk at >90%.  Maintain the percentage of children age 6-59 months who received a vitamin A supplement in the last 6 months at >90%  Increase the proportion of women who receive a dose of vitamin A supplement within 8 weeks of delivery from 20% to 40%  Increase the proportion of mothers who take iron supplementation for more than 90 days during pregnancy and the post-partum period from 10% to 30%  Increase the use of adequately iodised salt from 43% to 90% 1.4 STRATEGIC DIRECTION FOR THE PERIOD 2015 TO 2020 The implementation of health sector interventions during the period July 2015 to December 2016 will continue to be guided by Tanzania Development Vision 2025, Health Sector Policy 2007, and the Primary Health Care Service Development Programme (2007-2017). The Tanzania Development Vision 2025 document will continue to provide direction and philosophy for long-term development, whereas the National Health Policy will provide the focus for improving the planning and provision of health services in Tanzania. At the end of 2014, the MoHCDGEC started developing strategic documents to pick up from where the HSSP III (2009-2015), National Road Map Strategic Plan To Accelerate Reduction of Maternal, Newborn, and Child Deaths in Tanzania-One Plan (2008-2015), and the Sharpened One Plan (2014-2015) ended. The documents developed and launched are the Health Sector Strategic Plan IV 2015-2020 (HSSP IV 2015- 2020) and the National Road Map Strategic Plan To Improve Reproductive, Maternal, Newborn, Child, and Adolescent Health-One Plan II (2016-2020). These documents provide a framework to guide the provision, monitoring, and evaluation of reproductive, maternal, newborn, child, and adolescent health interventions for the period July 2015 to December 2020. Both the HSSP IV and One Plan II were developed in a participatory process under the leadership of the then Ministry of Health and Social Welfare (MoHSW). During this process, inputs were received from governmental, non-government, and private sector partners, with contributions from ministries, departments, and agencies, especially the Prime Minister’s Office for Regional Administration and Local Government (PMO-RALG) and from development partners. 1.4.1 Health Sector Strategic Plan IV (2015-2020) The overall objective of HSSP IV is to reach all households with essential health and social welfare services, to meet, as much as possible, the expectations of the population, adhering to objective quality 10 • Introduction and Survey Methodology standards, and applying evidence-informed interventions through efficient channels of service delivery. This objective will be realised through five strategic objectives: Strategic Objective 1: The health and social services sector will achieve objectively measurable quality improvement of primary health care services, delivering a package of essential services in communities and health facilities. Strategic Objective 2: The health and social welfare sector will improve equitable access to services in the country by focusing on geographic areas with higher disease burdens and vulnerable groups in the population with higher risks. Strategic Objective 3: The health and social welfare sector will achieve active community partnership through intensified interactions with the population for improvement of health and social wellbeing. Strategic Objective 4: The health and social welfare sector will achieve a higher rate of return on investment by applying modern management methods and engaging in innovative partnerships. Strategic Objective 5: To address the social determinants of health, the health and social welfare sector will collaborate with other sectors, and advocate for the inclusion of health promoting and health protecting measures in other sectors’ policies and strategies. 1.4.2 One Plan II (2016-2020) This strategy takes cognizance of the emphasis enshrined within Sustainable Development Goals (SDGs) and other international strategies. International strategies stress the importance of skilled, motivated, and enabled human resources for health, and other pillars of the health system for provision of quality reproductive health services. Furthermore, this strategy translates all national policies and strategies into an enabling environment to enhance pregnancy outcome via service provision, along the continuum of care, from pre-pregnancy to postpartum period; using antenatal and Emergency Obstetrics and Newborn Care (EmONC) interventions and services, and improved newborn and child health, through sustained gains of Millennium Development Goal (MDG) milestones. The overall goal of One Plan II is to improve reproductive, maternal, newborn, child and adolescent health (RMNCAH) in Tanzania in line with the National Development Vision 2025. This goal is planned to be realised through three key strategies: Key RMNCAH Strategy 1: Strengthen reproductive maternal, newborn, child, and adolescent health.  Strengthen maternal health and newborn health services, including family planning (FP); focused antenatal care (FANC); postnatal and newborn care; and emergency obstetrics and newborn care (EmONC).  Strengthen and improve visibility of adolescent reproductive health services including strengthening the adolescent health programme, improving its visibility, and developing and implementing a comprehensive strategy for adolescent health.  Scale up and expand the coverage for reproductive health (RH) services, including family planning, reproductive cancers, gender-based violence and violence against children, health needs of the elderly, fistula, and male reproductive health, including male involvement in reproductive health interventions. Key RMNCAH Strategy 2: Scale up the child health programme.  Scale up coverage of the immunization and vaccine development programme, care for the sick child, and emergency triage assessment and treatment. Introduction and Survey Methodology • 11  Strengthen the implementation of the Integrated Management of Child Illnesses (IMCI) interventions.  Scale up newborn, infant, and young child feeding services, including promotion of early breastfeeding, exclusive breastfeeding, and complementary feeding after 6 months. Key RMNCAH Strategy 3: Strengthen response to cross-cutting issues.  Strengthen RMNCAH interventions through the operationalization of annual One Plan II operational plans, and convening of annual RCH meetings.  Improve the availability of RMNCAH and nutrition commodities (RMNCH lifesaving commodities, family planning commodities, vaccines, therapeutic feeds, vitamin A for U5 children, and iron-folate supplements for pregnant women).  Strengthen community involvement in RMNCAH and nutrition services.  Provide comprehensive health promotion and education services in all RMNCAH programmes.  Strengthen the RMNCAH management information system and operational research activities. 1.4.3 National Key Result Area in Health Care In 2014, the National Key Result Area in Health Care was introduced, and four broad outcomes (key result areas) were identified with 22 initiatives to be implemented for 3 years, from 2015/16 to 2017/18, in order to achieve the set targets and goals. These initiatives are to be implemented in collaboration with the MoHCDGEC, PMO-RALG, President’s Office Public Service Management (PO-PSM), and Medical Stores Department (MSD). The four key results areas that were formulated in the Health and Social Welfare sector include: 1. Human Resources for Health (HRH) interventions aim to attain a 100% balanced distribution of skilled health workers at the primary level in 13 underserved regions by 2017-18. There are six distinct initiatives: prioritise allocation of employment permits to regions with a critical shortage of skilled HRH, provide skilled HRH through public-private partnerships and private sector engagement, and redistribute health workers within regions. Other goals are optimising the pool of new recruits, empowering the Local Government Authority (LGA) in human resource management, and synchronising the recruitment process at the central level. 2. Health commodities targets focus on ensuring 100% stock availability of essential medicines in all primary health facilities in the country. Six initiatives are to be implemented: (1) improving governance and accountability to the health commodity supply chain, (2) eliminating frequent stock outs and pilferages, and (3) strengthening the management of MSD’s working capital and complementing MSDs in the procurement and distribution of medicines through engagement with the private sector, therefore improving accountability. Other initiatives include introducing an Information and Communication Technology (ICT) mobile application platform, expanding the short message service (SMS) reporting system, and scaling up total quality management initiatives to the primary facility level using the 5S-KAIZEN approach. 3. Health facility performance management improvement goals include achieving 80% of primary health facilities at the 3-stars and above rating by 2017-18 in twelve identified priority regions. This is to be achieved through four initiatives: (1) assess, rate, and develop specific facility performance improvement plans for health facilities below a 3-star rating at the primary level with introduction of the star rating system of certification; (2) increase social accountability at facility and community levels, (3) introduce performance targets and contracts, and (4) implement decentralization of fiscal management from the council to health facility level. 12 • Introduction and Survey Methodology 4. Reproductive Maternal, Neonatal, Adolescent, and Child Health (RMNCAH) services target the achievement of a 20% reduction in maternal and neonatal mortality rates in five identified priority regions by 2017-18. The following six initiatives will be implemented to achieve the stated goals: (1) mobilise community health workers (CHWs) to improve RMNCAH services, (2) use m-Health (SMS) and Maternal CHW App (Internet) through Public Private Partnership (PPP), (3) expand Comprehensive Emergency Obstetric and Neonatal Care (CEmONC), (4) expand Basic Emergency Obstetric and Neonatal Care (BEmONC) services, (5) construct blood bank facilities at the regional level, and (6) develop integrated mass media campaigns through PPP. The RMNCAH services will be provided through a continuum of care to include family planning, antenatal care, labour and delivery, and care during the postnatal period for both mother and the newborn. Across the four key results areas there will be baseline assessments to get accurate starting information on data for target setting and assessment of performance. Baseline assessments will be conducted by the MoHCDGEC with collaboration from the respective LGAs. At all levels, there will be weekly reporting and monitoring of key performance indicators from facilities to the MoHCDGEC and to the President’s Office. Data for quarterly monitoring of the progress of the key results areas and other initiatives will be readily available for utilization in the Health Management Information System and the District Health Information System2 (DHIS 2) electronic data base. 1.5 OBJECTIVES AND SURVEY ORGANIZATION The 2015-16 Tanzania Demographic and Health Survey and Malaria Indicator Survey (TDHS-MIS) is the ninth in a series of national sample surveys conducted in Tanzania to measure levels, patterns, and trends in demographic and health indicators. The first TDHS, conducted in 1991-92, was followed by the 1994 Tanzania Knowledge, Attitudes, and Practices Survey (TKAPS), the 1996 TDHS, the 1999 Tanzania Reproductive and Child Health Survey (TRCHS), the 2003-04 Tanzania HIV/AIDS Indicator Survey (THIS), the 2004-05 TDHS, the 2007-08 Tanzania HIV/AIDS and Malaria Indicator Survey (THMIS), and the 2010 Tanzania Demographic and Health Survey (TDHS 2010). The 2015-16 Tanzania Demographic and Health Survey and Malaria Indicator Survey (TDHS-MIS) was undertaken by the National Bureau of Statistics (NBS) and the Office of Chief Government Statistician (OCGS), Zanzibar, in collaboration with the Ministry of Health, Community Development, Gender, Elderly, and Children on the Tanzania Mainland and the Ministry of Health, Zanzibar. Funding for the survey was provided by the Tanzania government through the Ministry of Health, Community Development, Gender, Elderly, and Children; Canadian Department of Foreign Affairs, Trade and Development (DFATD); United Nations Population Fund (UNFPA); Irish Aid; and United Nations Children’s Fund (UNICEF). Microscopic reading of malaria infection was conducted by the Ifakara Health Institute (IHI), while the Tanzania Food and Nutrition Centre (TFNC) tested women’s urine and household salt for the presence of iodine. ICF International provided technical assistance through the Demographic and Health Surveys (DHS) Program, which is funded by the United States Agency for International Development (USAID) which offers financial support and technical assistance for population and health surveys in countries worldwide. 1.5.1 Objectives The primary objective of the 2015-16 TDHS-MIS is to provide up-to-date estimates of basic demographic and health indicators. This survey collected information on fertility levels, marriage, sexual activity, fertility preferences, awareness and use of family planning methods, breastfeeding practices, nutrition, childhood and maternal mortality, maternal and child health, malaria, and other health-related issues. In addition, the 2015-16 TDHS-MIS provided estimates of anaemia prevalence among children age 6-59 months and women age 15-49 years, estimates of malaria prevalence among children age 6-59 months, and estimates of iodine concentration in household salt and women’s urine. Introduction and Survey Methodology • 13 The information collected through the 2015-16 TDHS-MIS is intended to assist policy makers and programme managers in evaluating and designing programmes and strategies to improve the health of the country’s population. 1.5.2 Survey Organization Sample design The sample design for the 2015-16 TDHS-MIS was done in two stages and was intended to provide estimates for the entire country, for urban and rural areas in Tanzania Mainland, and for Zanzibar. For specific indicators such as contraceptive use, the sample design allowed the estimation of indicators for each of the 30 regions (25 regions from Tanzania Mainland and 5 regions from Zanzibar). The first stage involved selecting sample points (clusters), consisting of enumeration areas (EAs) delineated for the 2012 Tanzania Population and Housing Census. A total of 608 clusters were selected. In the second stage, a systematic selection of households was involved. A complete households listing was carried out for all 608 selected clusters prior to the fieldwork. From the list, 22 households were then systematically selected from each cluster, yielding a representative probability sample of 13,376 households for the 2015-16 TDHS-MIS. To estimate geographic differentials for certain demographic indicators, Tanzania was divided into nine geographic zones. Although these zones are not official administrative areas, this classification system is also used by the Reproductive and Child Health Section of the MoHCDGEC. Grouping the regions into zones allowed a relatively large number of people in the denominator and a reduced sampling error. Note that the zones, defined below, differ slightly from the zones used in previous DHS surveys. Therefore, comparisons across the zones and from survey to survey should be made with caution. The zones are as follows: Western zone: Tabora, Kigoma Northern zone: Kilimanjaro, Tanga, Arusha Central zone: Dodoma, Singida, Manyara Southern Highlands zone: Iringa, Njombe, Ruvuma Southern zone: Lindi, Mtwara South West Highlands zone: Mbeya, Rukwa, Katavi Lake zone: Kagera, Mwanza, Geita, Mara, Simiyu, Shinyanga Eastern zone: Dar es Salaam, Pwani, Morogoro Zanzibar: Kaskazini Unguja, Kusini Unguja, Mjini Magharibi, Kaskazini Pemba, Kusini Pemba All women age 15-49 who were either usual residents or visitors in the household on the night before the survey were included in the 2015-16 TDHS-MIS and were eligible to be interviewed. In a subsample of one-third of all the households selected for the survey, all men age 15-49 were eligible to be interviewed if they were either usual residents or visitors in the household on the night before the survey. In all households, with the parent’s or guardian’s consent, children age 6-59 months were tested for anaemia and malaria. All interviewed women were tested for anaemia. In the households selected for interviews with men, interviewed women were asked to provide a urine sample and a sample of household salt for laboratory testing to detect the presence of iodine. 14 • Introduction and Survey Methodology Questionnaires Four questionnaires were used for the 2015-16 TDHS-MIS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, and the Biomarker Questionnaire. These questionnaires were based on the DHS Program’s standard Demographic and Health Survey (DHS) questionnaires. They were adapted to reflect the population and health issues relevant to Tanzania. Inputs were solicited from various stakeholders representing government ministries, departments, and agencies; non-governmental organizations; and development partners. After the preparation of the definitive questionnaires in English, the questionnaires were translated into Kiswahili. The Household Questionnaire was used to list all the usual members and visitors in the selected households. Basic demographic information was collected on the characteristics of each person listed, including his or her age, sex, marital status, education, and relationship to the head of the household. For children under age 18, their parents’ survival status was determined. The data on age and sex of household members obtained in the Household Questionnaire were used to identify women and men who were eligible for individual interviews. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as source of water, type of toilet facilities, materials used for the floor, roof, and exterior walls of the dwelling unit, ownership of various durable goods and assets, and ownership and use of mosquito nets. The Woman’s Questionnaire was used to collect information from all eligible women age 15-49. These women were asked questions on the following topics:  Background characteristics (age, education, media exposure)  Birth history and childhood mortality  Knowledge and use of family planning methods  Fertility preferences  Antenatal, delivery, and postnatal care  Breastfeeding and infant feeding practices  Vaccinations and childhood illnesses  Marriage and sexual activity  Women’s work and husbands’ background characteristics  Other health issues  Adult mortality, including maternal mortality  Malaria  Domestic violence The Man’s Questionnaire was administered to all men age 15-49 in the subsample of households selected for the men’s survey. The Man’s Questionnaire collected much of the same information found in the Woman’s Questionnaire but was shorter because it did not contain a detailed reproductive history or questions on maternal and child health. The Biomarker Questionnaire was used to record anthropometric measurements (height and weight) for children under age 5 and women age 15-49; record anaemia test results for children age 6-59 months and women age 15-49; record malaria rapid test results for children age 6-59 months; document responses to a request for blood samples among children age 6-59 months, to be tested later for malaria using microscopy at the Ifakara Health Institute lab; and document responses to request for a household salt sample and a urine sample among women age 15-49, to be tested later for iodine at the Tanzania Food and Nutrition Centre laboratory. Anthropometric Measurements, Testing for Malaria and Anaemia, Testing for Iodine Anthropometry: Height and weight measurements were recorded for children under age 5 and women age 15-49. Introduction and Survey Methodology • 15 Testing for Anaemia: Blood specimens for haemoglobin measurement were collected from women age 15-49 and from all children age 6-59 months for whom consent had been obtained from their parents or guardians. Blood samples were drawn from a drop of blood taken from a finger prick (or a heel prick in the case of children age 6-11 months) and collected in a microcuvette. Haemoglobin analysis was carried out on-site using a battery-operated portable HemoCue analyzer. Results were provided verbally and in writing. Parents/guardians of children with a haemoglobin level under 7 g/dl were instructed to take the child to a health facility for follow-up care. Likewise, nonpregnant women and pregnant women were referred for follow-up care if their haemoglobin levels were below 7 g/dl and 9 g/dl, respectively. Testing for Malaria: The 2015-16 TDHS-MIS collected finger- (or heel-) prick blood samples from children age 6-59 months to perform on-the-spot testing for malaria. Thick blood smears were also collected and taken to a laboratory to detect the presence of Plasmodium parasites. Malaria testing using a rapid diagnostic test (RDT). Another major objective of the 2015-16 TDHS- MIS was to provide information about the extent of malaria infection among children age 6-59 months. Using the same finger- (or heel-) prick used for anaemia testing, a drop of blood was tested immediately using the SD Bioline Pf/Pan RDT, which is a rapid diagnostic test for malaria. It tests for two antigens— one found in many species of Plasmodium (Pan) and the other specific to Plasmodium falciparum (Pf), the major cause of malaria in Tanzania. The test includes a disposable sample applicator that comes in a standard package. A tiny volume of blood is captured on an applicator and placed in the well of the testing device. All field nurses were trained to perform the RDT in the field, according to the manufacturers’ instructions. As with the anaemia testing, malaria RDT results were provided to the child’s parent or guardian in oral and written form and were recorded on the Biomarker Questionnaire. Children who tested positive for malaria using the RDT were offered a full course of treatment according to Tanzania national malaria treatment guidelines, provided they were not currently on treatment with Artemisinin Combination Therapy (ACT) and had not completed a full course of ACT during the 2 weeks preceding the survey. To ascertain the correct dose, nurses were provided with treatment guidance charts and were instructed to ask about signs of severe malaria and about any medications the child might already be taking. The nurses then provided the age-appropriate dose of ACT along with instructions on how to administer the medicine to the child3. Children who tested positive and showed symptoms of severe malaria (haemoglobin levels below 7 g/dl, extreme weakness, loss of consciousness, rapid breathing, seizures, bleeding, jaundice, and dark urine) were not offered the treatment. Because the first-line treatment for severe malaria is parenteral quinine, the parents or guardians of these children were advised to take them to a health facility immediately. The parents or guardians of all other children treated were told to take the child to a health facility immediately if they became sicker, developed a fever or difficulty breathing, or were not able to drink or breastfeed. They also received counselling on how to prevent malaria. Children who tested positive for malaria in Zanzibar were not treated due to the current procedure for malaria elimination on the island. Their parents or guardians were advised to take their children to the nearest health facility immediately. Malaria testing using blood smears: In addition to the RDT, thick smears were prepared in the field. Each blood smear slide was given a bar code label, with a duplicate affixed to the Biomarker Questionnaire. An additional copy of the bar code label was affixed to a blood sample transmittal form to track the blood samples from the field to the laboratory. The slides were dried in a dust-free environment and stored in slide boxes. The thick smear slides were collected regularly from the field, along with the 3 Dosage of ACT was based on recipient’s age. The proper dosage for a child age 6 months to 3 years is one tablet of artemether-lumefantrine (co-formulated tablets containing 20 mg of artemether and 120 mg of lumefantrine) to be taken twice daily for 3 days, while the dosage for a child age 4-7 is two tablets of artemether-lumefantrine to be taken twice daily for 3 days. 16 • Introduction and Survey Methodology completed questionnaires, and transported to Ifakara Health Institute laboratory in Bagamoyo for microscopic reading to determine presence of Plasmodium infection. Testing for Iodine Deficiency: The 2015-16 TDHS-MIS included several tests related to iodine. First, in all households, interviewers asked for a teaspoon of salt. The salt was tested for iodine using a simple rapid test kit. Salt that turned any shade of purple after being diluted with a drop of the test solution was considered to be iodised. Second, in every third sampled household, TDHS-MIS field teams asked for a slightly larger sample of household salt that was put into a screw-capped plastic container, appropriately labelled and transported to the Tanzania Food and Nutrition Centre (TFNC) lab, where it was then tested for iodine content. Third, interviewing teams requested that women respondents provide a urine sample for subsequent testing for iodine levels. Women who consented were provided with a small plastic cup in which to urinate. While in the field, the urine was transferred from the plastic cup via a vacuum method into small tubes with tightly fitted caps, ready for transport to the TFNC laboratory, where samples were tested for iodine. Pretest A pre-test was conducted in Tanga region from May 20, 2015, through June 18, 2015. Sixteen participants (12 women and 4 men) participated in the 4-week pre-test training and fieldwork practice for the 2015-16 TDHS-MIS. The majority of participants had worked in various TDHS activities previously. Training was conducted by trainers from National Bureau of Statistics (NBS), OCGS, and MoHCDGEC, with technical assistance from ICF International. Classroom instructions were provided during the first 3 weeks, and pre- test field practice took place for 5 days in two rural and two urban EAs. Following the field practice, a debriefing session was held with the pre-test field staff, and modifications to the questionnaires were made based on lessons learned from the pre-test exercise. Training of Field Staff The main training of the 2015-16 TDHS-MIS enumerators, supervisors, and editors took place in Kilimanjaro region from July 20, 2015, to August 21, 2015. A total of 74 female nurses, 20 male nurses, 20 supervisors, and 20 editors from all over the country were invited to participate in the training. The training sessions were conducted by NBS, Office of the Chief Government Statistician (OCGS), and trainers from ministries responsible for health on both Tanzania Mainland and Zanzibar with support from ICF International. Training on biomarkers was provided by trainers from Ifakara Health Institute (IHI) and Tanzania Food and Nutrition Centre (TFNC), with support from ICF International. Participants were evaluated through in-class exercises, quizzes, and observations made during field practice. By the end of the main training, 16 teams were formed, consisting of 16 individuals to serve as team leaders, 16 to serve as field editors, 16 as male interviewers, and 64 as female interviewers. All interviewers were nurses. The team leaders received additional training on how to identify the selected households, different subsamples, data quality control procedures, and fieldwork coordination. The field editors received additional training on how to edit the questionnaires, data quality control procedures, and how to enter data in tablets. 1.6 FIELDWORK Data collection was carried out by 16 field teams: three teams in Zanzibar and 13 teams on Tanzania Mainland. Each team was provided with a four-wheel drive vehicle with a driver. The teams consisted of a team supervisor, four female interviewers, one male interviewer, and one field editor, who also entered data into a tablet. The field editor and supervisor were responsible for reviewing all questionnaires for completeness, quality, and consistency before entering data into the tablet. All questionnaires, dried blood smears, table salt, and urine specimens were transferred to the NBS head office almost every 2 weeks by a Introduction and Survey Methodology • 17 quality control team from NBS, OCGS, TFNC, and ministries responsible for health for both Tanzania Mainland and Zanzibar. The dried blood smears, table salt and urine specimens were sent later to IHI and TFNC laboratories for testing. The NBS also coordinated and supervised all fieldwork activities. ICF International provided technical assistance during the entire 5-month data collection period, from August 22, 2015, through February 14, 2016. 1.6.1 2015-16 TDHS-MIS Field Challenges This section summarises the reports from the 2015-16 TDHS-MIS regional field teams, quality control, and field monitoring personnel on the challenges faced during the data collection exercise, August 2015 – March 2016. The main objective of this part is to specifically appreciate the extra efforts made by the various field teams in overcoming different field challenges while ensuring that the 2015-16 TDHS-MIS data collection undertaking was successfully implemented resulting in high quality data. Sharing this field experience with the general public is one way of honouring the data collection field teams and showing the public that the contained findings passed through delicate situations. Data collection started when Tanzania was having campaigns for the 2015 general elections. The campaigns started in August and lasted until October 2015. The teams’ schedules were planned in such a way that field work would start in areas known to have high political tensions with possible violence during political campaigns. This was one of the challenges faced by field teams; therefore they had to spend some time informing and convincing the general public that the survey was not in any way related to the forthcoming general elections. The survey also faced the common challenges of fieldwork in Tanzania, including rough roads. Remote areas are hard to reach and therefore field teams had to walk long distances while carrying their working- gear, which included weighing scales, length boards, and backpacks with questionnaires and other field supplies, to get to the selected households. Some of the clusters had scattered pastoralist and fishery households that forced interviewers to walk long distances and climb mountainous areas within the clusters with all their field supplies. In some of these areas, there were no appropriate places for meals and accommodation. In these places, enumerators cooked for themselves and used nearby school rooms and village offices for accommodation. Sometimes due to lack of accommodation, the enumerators (mainly male) spent nights inside the field vehicles. In addition, the survey data collection exercise extended to November/December 2015, which is the rainy season in most parts of the country. For this reason, members of the field teams sometimes had to walk long distances, as the roads were inaccessible by vehicles due to floods, broken bridges, and slippery surfaces. It is worth noting that the field teams were very committed to the task and worked diligently to ensure that all selected households were reached and successfully interviewed regardless of where they were or whether they were accessible by vehicle, motorcycle, bicycle, or by foot. In addition to all the challenges, interviewing sessions were long. Sometimes the interviewers stayed the whole day in the same households, especially if the households had more than three eligible women with maybe two to three children under age 5. The long questionnaires hindered interviewees from doing their daily activities, and hence sometimes they would want to leave. Interviewers had to take time to convince them of the importance of completing the session, as results would relate to the country development planning for the needs of the population. All of these described challenges for the 2015-16 TDHS-MIS field teams indicate that data collection is neither a science nor an art, rather a team commitment, requiring dedication and patriotism. Let us praise 18 • Introduction and Survey Methodology the field teams wherever they are for their good work and for maintaining the integrity of the data. They deserve the credit. 1.6.2 Data Processing In the 2015-16 TDHS-MIS the first data entry was done concurrently with data collection in the field. After the paper questionnaires were completed, edited, and checked by both the field editor and the supervisor, the data was entered into a tablet equipped with a data entry programme. This was done by the editor. Completed questionnaires were then sent to NBS headquarters, where they were entered for the second time and edited by data processing personnel who were given special training for this task. ICF International provided technical assistance during the entire data processing period. Processing the data concurrently with data collection allowed for regular monitoring of team performance and data quality. Field check tables were generated regularly during data processing to check various data quality parameters. As a result, feedback was given on a regular basis, encouraging teams to continue in areas of good performance and to correct areas in need of improvement. Feedback was individually tailored to each team. Data entry, which included 100% double entry to minimise keying errors, and data editing, were completed on March 21, 2016. Data cleaning and finalization were completed on April 22, 2016. 1.6.3 Response Rates Table 1.2 shows response rates for the Tanzania 2015-16 DHS-MIS. A total of 13,360 households were selected for the survey, of which 12,767 were occupied. Of the occupied households, 12,563 were successfully interviewed, yielding a response rate of 98%. In the interviewed households, 13,634 eligible women were identified for individual interviews; interviews were completed with 13,266 women, yielding a response rate of 97%. In the subsample of households selected for the male survey, 3,822 eligible men were identified and 3,514 were successfully interviewed, yielding a response rate of 92%. There is little variation in household response rates between rural and urban residences. LIST OF TABLES  Table 1.1 Selected demographic indicators from various sources, Tanzania 1967-2012  Table 1.2 Results of the household and individual interviews Introduction and Survey Methodology • 19 Table 1.1 Selected demographic indicators from various sources, Tanzania 1967-2012 Indicator Census Year 1967 1978 1988 2002 2012 Population (millions) 12.3 17.5 23.1 34.4 44.9 Intercensal growth rate (%) 2.6 3.2 2.8 2.9 2.7 Sex ratio 95.2 96.2 94.2 96.0 95.0 Crude birth rate 47 49 46 43 42 Total Fertility 6.6 6.9 6.5 6.3 5.5 Crude death rate 24 19 15 14 9.3 Infant mortality 155 137 115 95 46.2 % urban 6.4 13.8 18.3 23.1 29.6 Density (population/km2) 14 20 26 39 51 Life expectancy (years) 42 44 50 51 61.8 Male 6,005,339 8,586,713 11,327,511 16,829,861 21,869,990 Female 6,308,130 8,925,897 11,846,825 17,613,742 23,058,933 Source: NBS Table 1.2 Results of the household and individual interviews Number of households, number of interviews, and response rates, according to residence (unweighted), Tanzania 2015-16 Tanzania Mainland Zanzibar Tanzania Result Urban Rural Total Household interviews Households selected 3,570 8,008 11,578 1,782 13,360 Households occupied 3,364 7,639 11,003 1,764 12,767 Households interviewed 3,265 7,543 10,808 1,755 12,563 Household response rate1 97.1 98.7 98.2 99.5 98.4 Interviews with women age 15-49 Number of eligible women 3,750 7,714 11,464 2,170 13,634 Number of eligible women interviewed 3,606 7,521 11,127 2,139 13,266 Eligible women response rate2 96.2 97.5 97.1 98.6 97.3 Interviews with men age 15-49 Number of eligible men 1,054 2,239 3,293 529 3,822 Number of eligible men interviewed 945 2,079 3,024 490 3,514 Eligible men response rate2 89.7 92.9 91.8 92.6 91.9 1 Households interviewed/households occupied 2 Respondents interviewed/eligible respondents Housing Characteristics and Household Population • 21 HOUSING CHARACTERISTICS AND HOUSEHOLD POPULATION 2 Key Findings  Drinking water: Sixty-one percent of households in Tanzania have access to improved sources of drinking water: 86% of urban Mainland households, 49% of rural Mainland households, and 98% of households in Zanzibar. Access to improved sources of water in Tanzania has improved substantially since the 2010 TDHS (from 57% to 61%).  Sanitation: Only 19% of households use improved, non- shared toilet facilities. One in 10 households has no toilet at all.  Household population composition: The population of Tanzania is young, with 46% of the population under age 15.  Birth registration: Registration of children under age 5 has increased substantially, from 16% in 2010 to 26% in 2016.  Orphans: While eight percent of children under age 18 are orphans (one or both parents are dead), as many as 18% of children under age 18 do not live with either biological parent.  School attendance: The net attendance ratio drops from 76% in primary schools to 23% in secondary schools. Girls are more likely to attend primary school than boys, whereas there are no major differences by gender in secondary school attendance.  Health care expenditure: The total per capita annual expenditure for health services (outpatient visits and inpatient admissions combined) is higher for females than males (TZS 11,442 per woman and TZS 8,235 per man). nformation on the socioeconomic characteristics of the household population in the 2015-16 TDHS- MIS provides context to interpret demographic and health indicators and can furnish an approximate indication of the representativeness of the survey. In addition, this information sheds light on the living conditions of the population. This chapter presents information on source of drinking water, sanitation, exposure to smoke inside the home, housing characteristics, household wealth, hand washing, household population and composition, children’s living arrangements, birth registration, educational attainment, school attendance, food security, and health care expenditures. I 22 • Housing Characteristics and Household Population 2.1 DRINKING WATER SOURCES AND TREATMENT Improved sources of drinking water Include piped water, public taps, standpipes, tubewells, boreholes, protected dug wells and springs, rainwater, and bottled water Sample: Households Improved drinking water sources are essential to prevent water contamination, and likely make water safe to drink. In Tanzania, about 6 in 10 households (61%) get their drinking water from improved sources (Table 2.1). Nearly 9 in 10 Tanzania Mainland urban households (86%) obtain their drinking water from improved sources. In Zanzibar, nearly all households (98%) obtain their drinking water from improved sources, a substantial increase from 80% in 2010. The two most common sources of drinking water among Tanzania Mainland’s urban households are water piped directly into the household’s dwelling, yard, or plot (25%), and water piped to a neighbour (26%). Protected dug wells and public tap/standpipes are the next two most common sources (13% and 11%, respectively) (Figure 2.1). By contrast, more than half (52%) of Tanzania Mainland rural households obtain their drinking water from unimproved sources. The two most common sources of drinking water among Tanzania Mainland rural households are unprotected dug wells (24%) and surface water (18%). The next two most common sources are improved sources such as public taps/standpipes (17%) and protected dug wells (14%). Fetching drinking water is an additional chore that could be of great cost to household members, depending on the time spent to obtain it. Four in 10 households (40%) spend 30 minutes or longer (round trip) to fetch drinking water; the figure is 52% in rural Tanzania Mainland, compared with 19% in urban Tanzania Mainland and 14% in Zanzibar. About 6 in 10 households (62%) do not treat their water prior to drinking, but more than one-third (36%) use an appropriate treatment method (i.e., boiling, bleaching, filtering, and solar disinfecting). While Tanzania Mainland rural households are less likely to treat their water than Tanzania Mainland urban households boiling is the main method of treating water in all areas (43% in Tanzania Mainland urban areas compared with 23% in Tanzania Mainland rural areas and 22% in Zanzibar). Water is a necessity of life. Fifty-four percent of households using piped water or water from a tube well or bore hole did not have water for at least 1 day in the 2 weeks preceding the survey (Table 2.2). This percentage is higher in Tanzania Mainland urban households (61%) and in Zanzibar (58%) than in Tanzania Mainland rural households (45%). Trends: Household use of improved drinking water sources has been increasing over time, from 52% in the 2004-05 TDHS, to 54% in the 2010 TDHS, and then up to the current level of 61% in the 2015-16 TDHS-MIS. Figure 2.1 Household drinking water by residence 15 17 11 16 25 4 37 11 26 4 14 11 11 17 33 16 14 52 2 39 Tanzania Mainland Urban Tanzania Mainland Rural Zanzibar All Unimproved source Public tap/ standpipe Piped to neighbor Piped water into dwelling/yard Protected well or spring Percent distribution of households by source of drinking water Housing Characteristics and Household Population • 23 2.2 SANITATION Improved toilet facilities Include any non-shared toilet of the following types: flush/pour flush toilets to piped sewer systems, septic tanks, and pit latrines; ventilated improved pit (VIP) latrines; pit latrines with slabs, and composting toilets. Sample: Households About one in five households in Tanzania (19%) use improved toilet facilities, defined as non-shared facilities that prevent people from coming into contact with human waste and thus reduce the transmission of cholera, typhoid, and other diseases (Table 2.3). Shared toilet facilities of an otherwise acceptable type are especially common in Tanzania Mainland urban areas (42%). One in ten households do not use any toilet facility (Figure 2.2). The most commonly used improved toilet facility in Tanzania Mainland urban areas is a flush toilet or pour flush to pit latrine (16%) and in Zanzibar, it is a pit latrine with slab (27%) (Table 2.3). Use of improved non-shared toilet facilities is much higher among households in Zanzibar (59%) than in urban and rural Tanzania Mainland (35% and 10%, respectively). Eighty six percent of Tanzania Mainland rural households use unimproved toilet facilities or have no toilet facilities at all, which increases the risk of disease transmission. By contrast, 23% of households in Tanzania Mainland urban areas and 27% of households in Zanzibar use unimproved toilet facilities or have no toilet facilities at all (Figure 2.2). Trends: Use of improved non-shared toilet facilities has increased over time from 2% in 2004-05 TDHS to 13% in the 2010 TDHS, and further to 19% in 2015-16. While slowly declining, the percent of households using unimproved toilet facilities are still in the majority. The percent decreased from 96% in 2004-05 TDHS to 76% in 2011-12, to the current level of 65%. 2.3 EXPOSURE TO SMOKE INSIDE THE HOME Exposure to smoke, either from cooking with solid fuels or from smoking tobacco, has potentially harmful health effects. More than 9 in 10 households in Tanzania (94%) use some type of solid fuel for cooking, mostly wood (66%), and charcoal (27%) (Table 2.4). Use of wood has decreased and charcoal increased in the previous five years; the 2010 TDHS reported 74% of households using wood and 21% using charcoal. Exposure to cooking smoke is greater when cooking takes place inside the house rather than in a separate building or outdoors. In Tanzania, cooking takes place inside the house in about one-third of households (33%). Additionally, in 16% of households someone smokes inside the house daily. 2.4 HOUSING CHARACTERISTICS The 2015-16 TDHS-MIS also collected information on other household characteristics, including access to electricity, flooring materials, and the number of rooms used for sleeping. Nationally, about one-quarter of households (23%) have electricity, ranging from a low of 5% in Tanzania Mainland rural households, up to Figure 2.2 Household toilet facilities by residence 2 13 17 10 21 73 11 55 42 4 14 16 35 10 59 19 Tanzania Mainland Urban Tanzania Mainland Rural Zanzibar All Improved facility Shared facility Unimproved facility No facility/bush/field Percent distribution of households by type of toilet facilities 24 • Housing Characteristics and Household Population 47% of households in Zanzibar, and 56% of Tanzania Mainland urban households. Access to electricity has increased in all three areas; the 2010 TDHS estimated that 3% of Tanzania Mainland rural households, 45% of Tanzania Mainland urban households, and 35% of Zanzibar households had electricity, respectively. Earth and sand are the most common flooring materials in Tanzania (57%), followed by cement (38%). Earth or sand flooring is most often used in three-quarters of Tanzania Mainland rural households (77%), while cement is the most common flooring material in Tanzania Mainland urban households (69%) and in Zanzibar (60%) Table 2.4 provides information on other housing characteristics. Household Durable Goods The survey also collected information on household effects, means of transportation, and ownership of agricultural land and farm animals. About 8 in 10 households (78%) own a mobile phone; about half (52%) own a radio, and one in five (20%) own a television. Only 9% of households own a refrigerator, 4% own a computer, and less than 1% own a non-mobile telephone. Possession of these household effects is substantially higher among households in Tanzania Mainland urban areas and in Zanzibar than among Tanzania Mainland rural areas. In contrast, Tanzania Mainland rural households are more likely to own agricultural land (80%) or farm animals (69%) than Tanzania Mainland urban households (30% each) and Zanzibar households (29% and 48%, respectively). A bicycle is the most common means of transport, especially among households in Zanzibar (52%) and in Tanzania Mainland rural areas (43%). For information on household durable goods, see Table 2.5. 2.5 HOUSEHOLD WEALTH Wealth index Households are given scores based on the number and kinds of consumer goods they own, ranging from a television to a bicycle or car, plus housing characteristics, such as source of drinking water, toilet facilities, and flooring materials. These scores are derived using principal component analysis. National wealth quintiles are compiled by assigning the household score to each usual (de jure) household member, ranking each person in the household population by their score, and then dividing the distribution into five equal categories, each with 20% of the population. Sample: Households Because more than 95% of the population lives on Tanzania Mainland, the Mainland population is evenly distributed among the five wealth quintiles. The distribution is a function of how the quintiles are constructed. Generally, the urban population in Tanzania Mainland is wealthier than the rural population. Eighty-eight percent of the urban population is in the two highest wealth quintiles, while 8 in ten of the rural population is in the three lowest wealth quintiles. (Figure 2.3). In Zanzibar, almost 80 percent of the population is in the two highest wealth quintiles (Table 2.6). By zone, 8 in 10 people in the Western zone are in the three lowest quintiles. Conversely, more than five in 10 people in the Northern zone (55%) and more than seven in 10 people in the Eastern zone (75%) are in the two highest wealth quintiles. Table 2.6 also shows the distribution of the population by wealth quintile within each region. Figure 2.3 Household wealth by residence 58 4 30 16 5 26 2 27 5 26 Urban Rural Percent distribution of de jure population by wealth quintiles Poorest Second Middle Fourth Wealthiest Housing Characteristics and Household Population • 25 2.6 HAND WASHING To obtain hand-washing information, interviewers asked permission to see the place where members of the household most often wash their hands. A place for washing hands was observed in more than 8 in 10 households (81%), ranging from 31 percent in Kaskazini Pemba to 99% in Katavi. Soap and water—the ideal hand washing agent—was seen in 59% of the hand-washing locations that were observed; another 37% had water only (Table 2.7). No water, soap, or other cleaning agents were observed in 3% of handwashing locations. 2.7 HOUSEHOLD POPULATION AND COMPOSITION Household A person or group of related or unrelated persons who live together in the same dwelling unit(s), who acknowledge one adult male or female as the head of the household, who share the same housekeeping arrangements, and who are considered a single unit. De facto population All persons who stayed in the selected households the night before the interview (whether usual residents or visitors). Tables in this report are based on de facto populations, unless otherwise stated. De jure population All persons who are usual residents of the selected households, whether or not they stayed in the household the night before the interview A total population of 59,657 individuals stayed overnight in 12,563 interviewed households in the 2015-16 TDHS-MIS. Fifty-two percent of them (30,904) were female, and 48% (28,753) were male (Table 2.8). Nearly half the population is under age 15 (46%), while only 4% are age 65 and older. The population pyramid in Figure 2.4 shows the population distribution by 5-year age groups, separately for males and females. The broad base of the pyramid illustrates that Tanzania’s population is young, which is typical of countries with low life expectancy and high fertility. The average household size in Tanzania is five people (mean size of 4.9) (Table 2.9). Tanzania Mainland urban households are slightly smaller (4.3 people per household) than Tanzania Mainland rural households (5.1 people per household) and those in Zanzibar (5.4 people). Women head 25% of all households. Trends: The age-sex structure of the Tanzanian population has remained rather constant over the past decade. The percentage of children under age 15 has remained at similar levels (47%) and that of Figure 2.4 Population pyramid 20 16 12 8 4 0 4 8 12 16 20 <5 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80+ Age Percent distribution of the household population Male Female 20 16 12 8 4 26 • Housing Characteristics and Household Population population age 65 and over has remained at 4% since 2004-05 TDHS. The 2004-05 TDHS also estimated the average household size to be 4.9 and found one-quarter of households to be female-headed. 2.8 CHILDREN’S LIVING ARRANGEMENTS AND PARENTAL SURVIVAL Orphan A child with one or both parents dead Sample: Children under age 18 In Tanzania, 8% of children under 18 are orphans, meaning that one or both of their parents are dead (Table 2.10). The percentage of orphans increases with age, ranging from 1% of children under age 2 to 18% of children age 15-17 (Figure 2.5). By zone, orphanhood is highest in Southern Highlands (12%). Across regions, it is highest in Iringa (13%), Ruvuma (12%), and Mara (12%). There are no major variations in orphanhood by sex, residence, or wealth. For information on school attendance by survivorship of parents, see Table 2.12. Trends: The percentage of children under age 18 who are orphans has dropped from 10% in the 2010 TDHS to 8% in the 2015-2016 TDHS-MIS. 2.9 BIRTH REGISTRATION Registered birth Child has a birth certificate or his/her birth has been registered with the civil authority. Sample: De jure children under age 5 Respondents were asked whether they had birth certificates for the children in the household who were under age 5. If they did not have a birth certificate, they were asked whether the birth had been registered with the civil authority. The 2015-16 TDHS found that 14% of children had birth certificates and 12% did not have birth certificates but had been registered. In total, 26% of children under age 5 had been registered with the civil authority (Table 2.11). Boys and girls under age 5 are equally likely to be registered. Boys under age 5 are slightly more likely to be registered than girls (29% versus 25%). The registration of births is more common in Tanzania Mainland urban areas (50%) than in Tanzania Mainland rural areas (16%). The registration of births in Tanzania Mainland is lower than in Zanzibar (25% versus 92%). The percentage of registered births increases with the household wealth quintile, from 8% in the lowest wealth quintile to 65% in the highest wealth quintile. Trends: Registration of children has increased from 16% in 2010 to 26% in 2016. 2.10 EDUCATION Education is one of the most important aspects of social and economic development. Education improves capabilities and is strongly associated with various socio-economic variables such as life-style, income, and fertility for both individuals and societies. Figure 2.5 Orphanhood by age 1 3 7 13 18 8 <2 2-4 5-9 10-14 15-17 0-17 Percentage of children under age 18 with one or both parents dead Housing Characteristics and Household Population • 27 2.10.1 Educational Attainment Median educational attainment Number of years of schooling completed by half of the population Sample: De facto household population age 6 and older Overall, about 1 in 4 females (24%) age 6 and older have no formal education, compared with about 1 in 5 males (19%). However, once girls and boys enter school, their completion rates are similar. One in 3 females and 1 in 3 males have completed primary school (32%), 7-8% of females and males have completed secondary education, and 1-2% of females and males have completed beyond secondary education (Table 2.13.1 and 2.13.2). The median number of years of schooling completed among females is 4.5 years and 5.1 years among males. Trends: The percentage of the population with no education has been decreasing over time, from 46 % of females and 34% of males in 1991-92 TDHS to 24% of females and 19% of males in 2015-16 TDHS. Patterns by background characteristics  Urban residents are more likely to complete secondary school than rural residents. For example, 15% of females in urban areas have completed secondary school compared with 4% of females in rural areas. Similarly, 18% of males in urban areas have completed secondary school compared with 4% of males in rural areas. Similar patterns are observed for education beyond secondary school.  Mainland and Zanzibar residents are similar in the percentages that have completed primary or gone on for further schooling, 48% in Mainland and 50% in Zanzibar among males, and similar percentages among females. The difference is that more students in Mainland stop after completing primary school and more students in Zanzibar go on for secondary or higher education.  Educational attainment increases steadily with household wealth among both females and males. The median number of years of schooling increases by about one or two years of schooling for each increase in the wealth quintile, from a low or 1 or 2 years to 7 years among the highest wealth quintile for both females and males. 2.10.2 School Attendance Net attendance ratio (NAR) Percentage of the school-age population that attends primary or secondary school Sample: Children age 7-13 for primary school NAR and children age 14-17 for secondary school NAR Gross attendance ratio (GAR) The total number of primary and secondary school students expressed as a percentage of the official primary and secondary school-age population Sample: Everyone age 5-24. Seventy-eight percent of girls age 7 to 13 are attending primary school compared with 73% of boys (Table 2.14). The net attendance ratio drops drastically in secondary school: only 24% of girls and 22% of boys are attending secondary school. 28 • Housing Characteristics and Household Population Patterns by background characteristics  Children in urban areas are more likely to be attending primary school than children in rural areas, (86% versus 72%). Similar patterns exist for secondary school attendance: NAR is 36% in urban areas and 16% in rural areas.  In 24 of the 30 regions, primary school attendance is higher among girls than boys.  The net attendance ratio increases steadily and dramatically with increasing wealth quintile for both primary and secondary schooling. The net attendance ratio for primary school children increases from 59% in the lowest quintile to 91% in the highest quintile, and for secondary school children it increases from 6% to 41% (Figure 2.6). Other Measures of School Attendance The TDHS-MIS education data allow the calculation of two more education indicators: the gross attendance ratio (GAR), and the gender parity index (GPI).The GAR, measures participation at each level of schooling for the de facto household population, as a percentage of the official school age population for that level. The GAR is 90% at the primary school level and 29% at the secondary school level. These figures indicate that not all children who should be attending primary or secondary school are doing so. The gender parity index (GPI), which is the ratio of female to male attendance rates, is slightly higher than one for both primary and secondary school. This confirms that there is relatively little difference in overall school attendance by boys and girls at the primary and secondary level. For more information on these indicators, see Table 2.14. 2.11 HOUSEHOLD FOOD SECURITY Household food security All Tanzanians should have access to safe food of sufficient quantity and quality at all times. Sample: Households The survey asked about the number of meals that household members usually consume every day, number of days they consumed meat or fish during the preceding week, and the frequency of problems satisfying food needs in the past year. Two percent of Tanzania Mainland households, both urban and rural, usually have only one meal a day (Table 2.15). Urban households are much more likely than rural households to have three or more meals a day (77% and 55%, respectively). Six in 10 households in Zanzibar have at least three meals a day. Nationally, only 57% of households reported that they never had a problem satisfying their food needs in the past year. Figure 2.6 Primary and secondary school attendance by wealth quintile 59 70 79 86 91 76 6 10 17 32 41 23 Lowest Second Middle Fourth Highest Total Primary Secondary WealthiestPoorest Housing Characteristics and Household Population • 29 2.12 HEALTH EXPENDITURES Annual per capita expenditure (in TZS) on outpatient and inpatient admissions Out-of-pocket health spending per person Sample: Household population The Tanzanian Government signed the Abuja Declaration in 2001 (Tanzania Abuja + 12 fact sheet), which commits the government to spending 15% of the total government budget on health. Spending more on health services, and spending more effectively, has a positive impact on other segments of the economy. The TDHS-MIS asked household respondents to identify how much they spent out of their own pockets for health care. Nationally, the per capita out-of-pocket health expenditure is TZS 8,235 among men and TZS 11,442 among women (Table 2.17). The per capita expenditure among men is higher for outpatient visits (TZS 4,795) than for inpatient admissions (TZS 3,440). As is the case of men, expenditures for outpatient visits are higher than for inpatient admissions (TZS 7,695 and TZS 3,748, respectively). With the exception of women in the lowest wealth quintile, per capita health expenditures increase with increasing wealth quintile and are significantly higher in the highest wealth quintile. Health expenditures are especially high among women in the lowest and two highest wealth quintiles (Figure 2.7). Figure 2.7 Per capita expenditure by household wealth quintile 9,763 6,256 8,202 10,476 22,296 3,085 5,011 6,302 9,954 17,007 0 5,000 10,000 15,000 20,000 25,000 Lowest Second Middle Fourth Highest Health expenditure per capita (in TZS) Female Male WealthiestPoorest 30 • Housing Characteristics and Household Population LIST OF TABLES For detailed information on household population, housing characteristics, and health expenditures, see the following tables:  Table 2.1 Household drinking water  Table 2.2 Availability of water  Table 2.3 Household sanitation facilities  Table 2.4 Household characteristics  Table 2.5 Household possessions  Table 2.6 Wealth quintiles  Table 2.7 Hand washing  Table 2.8 Household population by age, sex, and residence  Table 2.9 Household composition  Table 2.10 Children’s living arrangements and orphanhood  Table 2.11 Birth registration of children under age 5  Table 2.12 School attendance by survivorship of parents  Table 2.13.1 Educational attainment of the female household population  Table 2.13.2 Educational attainment of the male household population  Table 2.14 School attendance ratios  Table 2.15 Household food security  Table 2.16 Annual outpatient visits and inpatient admissions  Table 2.17 Annual per capita expenditure (in TZS) on outpatient visits and inpatient admissions  Table 2.18 Annual total health expenditure (in TZS) per household Housing Characteristics and Household Population • 31 Table 2.1 Household drinking water Percent distribution of households and de jure population by source of drinking water, time to obtain drinking water, and treatment of drinking water, according to residence, Tanzania DHS-MIS 2015-16 Households Population Tanzania Mainland Zanzibar Tanzania Tanzania Mainland Zanzibar Tanzania Characteristic Urban Rural Total Urban Rural Total Source of drinking water Improved source 86.0 47.8 60.4 97.9 61.4 86.4 47.0 58.6 97.6 59.7 Piped into dwelling/yard plot 24.8 3.6 10.6 37.2 11.3 25.6 3.0 9.6 38.0 10.4 Piped to neighbour 25.6 4.2 11.3 13.5 11.4 23.7 3.5 9.4 12.4 9.5 Public tap/standpipe 11.1 17.0 15.1 32.9 15.5 11.7 16.5 15.1 32.7 15.6 Tube well or borehole 4.9 4.6 4.7 2.1 4.6 5.0 4.4 4.6 1.8 4.5 Protected dug well 12.6 13.6 13.2 10.6 13.2 14.2 15.1 14.8 11.6 14.7 Protected spring 2.3 3.4 3.1 0.0 3.0 2.8 3.3 3.1 0.0 3.0 Rain water 1.0 1.3 1.2 0.1 1.2 1.2 1.3 1.2 0.1 1.2 Bottled water, improved source for cooking/ washing1 3.6 0.1 1.2 1.5 1.3 2.3 0.0 0.7 0.8 0.7 Unimproved source 13.8 52.2 39.5 2.1 38.5 13.4 52.9 41.4 2.4 40.3 Unprotected dug well 4.3 23.5 17.2 1.1 16.8 4.5 24.3 18.5 1.3 18.0 Unprotected spring 1.7 9.7 7.0 0.4 6.9 1.7 9.5 7.2 0.5 7.0 Tanker truck/cart with small tank 5.6 0.6 2.3 0.3 2.2 5.1 0.5 1.9 0.3 1.8 Surface water 1.1 18.3 12.6 0.1 12.3 1.5 18.5 13.5 0.1 13.2 Bottled water, unimproved source for cooking/ washing1 1.0 0.1 0.4 0.2 0.4 0.5 0.0 0.2 0.2 0.2 Other 0.2 0.0 0.1 0.0 0.1 0.2 0.0 0.1 0.0 0.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Time to obtain drinking water (round trip) Water on premises 60.2 11.9 27.9 57.0 28.6 59.5 10.7 25.0 57.1 25.9 Less than 30 minutes 21.3 35.9 31.1 29.5 31.0 20.4 34.8 30.6 28.9 30.5 30 minutes or longer 18.5 52.2 41.1 13.5 40.4 20.1 54.5 44.4 13.9 43.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Water treatment prior to drinking2 Boiled 42.7 22.8 29.4 21.8 29.2 43.3 21.7 28.0 21.1 27.8 Bleach/chlorine added 5.2 1.3 2.6 2.6 2.6 5.5 1.2 2.4 3.2 2.5 Strained through cloth 11.3 9.6 10.2 1.2 9.9 11.9 11.7 11.7 1.4 11.5 Ceramic, sand or other filter 1.3 0.6 0.9 0.6 0.8 1.4 0.6 0.9 0.6 0.9 Solar disinfection 0.1 0.1 0.1 0.0 0.1 0.2 0.1 0.1 0.0 0.1 Let it stand and settle 8.0 4.0 5.3 10.7 5.5 7.8 3.8 4.9 10.4 5.1 Other 1.6 0.5 0.8 0.8 0.8 1.1 0.5 0.7 0.6 0.6 No treatment 46.8 68.6 61.4 67.5 61.5 46.2 67.8 61.5 67.9 61.7 Percentage using an appropriate treatment method3 49.0 29.4 35.9 24.1 35.6 50.3 30.3 36.2 24.0 35.8 Number 4,053 8,195 12,247 316 12,563 17,349 41,888 59,237 1,713 60,950 1 Because the quality of bottled water unknown, households using bottled water for drinking are classified as using an improved or unimproved source according to their water source for cooking and washing. 2 Respondents may report multiple treatment methods so the sum of treatment may exceed 100 percent. 3 Appropriate water treatment methods include boiling, bleaching, filtering, and solar disinfecting. 32 • Housing Characteristics and Household Population Table 2.2 Availability of water Among households and de jure population using piped water or water from a tube well or borehole, percentage with lack of availability of water in the last 2 weeks, according to residence, Tanzania DHS-MIS 2015-16 Households Population Availability of water in last 2 weeks Tanzania Mainland Zanzibar Tanzania Tanzania Mainland Zanzibar Tanzania Urban Rural Total Urban Rural Total Not available for at least 1 day 60.5 45.1 53.4 57.8 53.6 62.2 44.9 53.6 59.8 54.0 Available with no interruption of at least 1 day 37.8 53.6 45.2 41.6 45.0 36.5 54.1 45.2 39.8 44.9 Don’t know/missing 1.6 1.3 1.5 0.6 1.4 1.4 1.0 1.2 0.4 1.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number using piped water or water from a tube well2 2,790 2,419 5,210 274 5,483 11,720 11,466 23,186 1,461 24,648 1 Households reporting piped water or water from a tube well or borehole as their main source of drinking water. Households reporting bottled water as their main source of drinking water are also included if their main source of water for cooking and handwashing is piped water or water from a tube well or borehole. Table 2.3 Household sanitation facilities Percent distribution of households and de jure population by type and location of toilet/latrine facilities, according to residence, Tanzania DHS-MIS 2015-16 Households Population Type and location of toilet/latrine facility Tanzania Mainland Zanzibar Tanzania Tanzania Mainland Zanzibar Tanzania Urban Rural Total Urban Rural Total Improved, not shared facility Flush/pour flush to piped sewer system 1.2 0.1 0.5 0.3 0.5 1.3 0.1 0.4 0.2 0.4 Flush/pour flush to septic tank 4.5 0.6 1.9 0.3 1.9 5.6 0.5 2.0 0.3 1.9 Flush/pour flush to pit latrine 16.3 2.0 6.7 25.0 7.2 19.6 1.8 7.0 26.5 7.6 Ventilated improved pit (VIP) latrine 2.1 0.5 1.1 6.3 1.2 2.5 0.6 1.2 6.7 1.3 Pit latrine with slab 10.7 6.5 7.9 26.8 8.4 12.9 6.4 8.3 27.3 8.8 Composting toilet 0.0 0.1 0.1 0.0 0.1 0.0 0.1 0.1 0.0 0.1 Tanzania 34.9 9.8 18.1 58.7 19.1 41.9 9.5 19.0 61.0 20.1 Shared facility1 Flush/pour flush to piped sewer system 0.6 0.0 0.2 0.2 0.2 0.4 0.0 0.1 0.2 0.1 Flush/pour flush to septic tank 2.2 0.1 0.8 0.2 0.8 1.8 0.1 0.6 0.1 0.5 Flush/pour flush to pit latrine 16.8 1.0 6.2 5.5 6.2 13.0 0.7 4.3 3.8 4.3 Ventilated improved pit (VIP) latrine 3.9 0.4 1.5 1.7 1.6 2.9 0.3 1.1 1.4 1.1 Pit latrine with slab 18.5 2.4 7.7 6.3 7.7 14.5 1.8 5.5 5.8 5.5 Tanzania 42.0 3.9 16.5 13.8 16.4 32.5 2.8 11.5 11.2 11.5 Unimproved facility Flush/pour flush not to sewer/septic tank/pit latrine 0.6 0.0 0.2 5.4 0.4 0.6 0.0 0.2 5.6 0.3 Pit latrine with slab (non- washable ) 15.3 52.6 40.3 4.6 39.4 16.4 52.7 42.0 4.0 41.0 Pit latrine without slab/open pit 5.2 20.2 15.2 0.7 14.9 6.1 21.1 16.7 0.8 16.2 Bucket 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 No facility/bush/field 2.0 13.0 9.4 16.6 9.5 2.5 13.5 10.3 17.3 10.5 Other 0.0 0.5 0.3 0.1 0.3 0.0 0.4 0.3 0.1 0.3 Tanzania 23.2 86.4 65.4 27.4 64.5 25.5 87.7 69.5 27.8 68.3 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of households/population 4,053 8,195 12,247 316 12,563 17,349 41,888 59,237 1,713 60,950 Location of toilet facility In own dwelling 18.1 2.0 7.8 81.7 9.5 19.5 1.7 7.4 83.5 9.4 In own yard/plot 79.8 89.5 86.0 15.3 84.4 78.4 90.7 86.8 13.9 84.9 Elsewhere 2.2 8.4 6.2 3.0 6.1 2.1 7.6 5.8 2.6 5.7 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Households/population with a toilet/latrine facility 3,972 7,128 11,100 263 11,364 16,922 36,213 53,136 1,417 54,553 1 Facilities that would be considered improved if they were not shared by two or more households. Housing Characteristics and Household Population • 33 Table 2.4 Household characteristics Percent distribution of households by housing characteristics, percentage using solid fuel for cooking, and percent distribution by frequency of smoking in the home, according to residence, Tanzania DHS-MIS 2015-16 Housing characteristic Tanzania Mainland Zanzibar Tanzania Urban Rural Total Electricity Yes 55.9 5.1 21.9 47.2 22.5 No 44.1 94.9 78.1 52.8 77.5 Total 100.0 100.0 100.0 100.0 100.0 Flooring material Earth, sand 17.5 77.1 57.4 23.3 56.5 Dung 0.0 0.5 0.3 0.1 0.3 Wood/planks 0.0 0.0 0.0 0.0 0.0 Palm/bamboo 0.0 0.0 0.0 0.0 0.0 Parquet or polished wood 0.0 0.0 0.0 0.1 0.0 Vinyl or asphalt strips 0.3 0.0 0.1 0.0 0.1 Ceramic tiles 9.9 0.6 3.7 9.6 3.8 Cement 68.6 21.3 37.0 59.9 37.5 Carpet 3.5 0.3 1.4 7.0 1.5 Other 0.2 0.1 0.1 0.1 0.1 Total 100.0 100.0 100.0 100.0 100.0 Rooms used for sleeping One 40.3 29.3 32.9 21.5 32.7 Two 30.7 38.8 36.1 32.2 36.0 Three or more 29.0 31.9 31.0 46.3 31.3 Total 100.0 100.0 100.0 100.0 100.0 Place for cooking In the house 43.5 28.5 33.4 65.8 34.2 In a separate building 23.7 56.0 45.3 15.3 44.5 Outdoors 30.7 15.0 20.2 17.2 20.1 No food cooked in household 2.2 0.6 1.1 1.6 1.1 Total 100.0 100.0 100.0 100.0 100.0 Cooking fuel Electricity 1.3 0.1 0.5 1.3 0.5 LPG/natural gas/biogas 7.7 0.5 2.9 2.6 2.9 Kerosene 5.3 0.3 1.9 1.6 1.9 Charcoal 63.1 9.3 27.1 30.3 27.2 Wood 20.4 89.2 66.4 62.5 66.3 Straw/shrubs/grass 0.0 0.1 0.1 0.1 0.1 Animal dung 0.0 0.0 0.0 0.0 0.0 No food cooked in household 2.2 0.6 1.1 1.6 1.1 Total 100.0 100.0 100.0 100.0 100.0 Percentage using solid fuel for cooking1 83.4 98.6 93.6 92.8 93.6 Frequency of smoking in the home Daily 11.5 18.1 15.9 7.7 15.7 Weekly 1.4 1.8 1.7 0.9 1.6 Monthly 0.1 0.1 0.1 0.1 0.1 Less than once a month 1.4 0.9 1.1 0.3 1.1 Never 85.6 79.1 81.2 91.0 81.5 Total 100.0 100.0 100.0 100.0 100.0 Number 4,053 8,195 12,247 316 12,563 LPG = Liquefied petroleum gas 1 Includes Kerosene, charcoal, wood, straw/shrubs/grass, , and animal dung 34 • Housing Characteristics and Household Population Table 2.5 Household possessions Percentage of households possessing various household effects, means of transportation, agricultural land, and livestock/farm animals by residence, Tanzania DHS-MIS 2015-16 Tanzania Mainland Zanzibar Total Possession Urban Rural Tanzania Household effects Radio 63.3 45.8 51.5 62.4 51.8 Television 46.6 6.4 19.7 39.6 20.2 Mobile phone 92.3 70.3 77.6 93.4 78.0 Computer 10.3 0.6 3.8 8.2 3.9 Non-mobile telephone 1.4 0.2 0.6 1.2 0.6 Refrigerator 22.1 1.3 8.2 29.5 8.7 Means of transport Bicycle 30.1 42.9 38.7 52.2 39.0 Animal drawn cart 1.6 3.9 3.1 2.2 3.1 Motorcycle/scooter 11.5 7.9 9.1 15.9 9.2 Car/truck 8.8 0.9 3.5 7.8 3.6 Boat with a motor 0.2 0.2 0.2 0.9 0.2 Ownership of agricultural land 29.8 80.1 63.5 28.8 62.6 Ownership of farm animals1 30.0 69.1 56.2 47.5 56.0 Number 4,053 8,195 12,247 316 12,563 1 Cows, bulls, other cattle, horses, donkeys, mules, goats, sheep, chickens, or other poultry Housing Characteristics and Household Population • 35 Table 2.6 Wealth quintiles Percent distribution of the de jure population by wealth quintiles, and the Gini Coefficient, according to residence and region, Tanzania DHS-MIS 2015-16 Wealth quintile Total Number of persons Gini coefficient Residence/region Lowest Second Middle Fourth Highest Residence Urban 4.9 2.1 5.2 29.6 58.3 100.0 17,856 0.19 Rural 26.3 27.4 26.2 16.0 4.1 100.0 43,094 0.40 Tanzania Mainland/Zanzibar Mainland 20.6 20.4 20.2 19.6 19.2 100.0 59,237 0.37 Urban 5.0 2.1 5.2 30.0 57.6 100.0 17,349 0.20 Rural 27.0 28.0 26.4 15.3 3.3 100.0 41,888 0.40 Zanzibar 0.7 6.0 14.1 32.4 46.8 100.0 1,713 0.39 Unguja 0.3 1.5 8.6 30.5 59.2 100.0 1,150 0.31 Pemba 1.6 15.4 25.3 36.3 21.5 100.0 563 0.54 Zone Western 35.8 27.8 18.1 10.2 8.1 100.0 6,278 0.61 Northern 13.1 13.2 18.2 26.9 28.5 100.0 6,579 0.41 Central 33.8 21.3 22.0 17.2 5.8 100.0 6,905 0.29 Southern Highlands 10.8 18.1 26.3 26.8 17.9 100.0 3,827 0.47 Southern 18.3 30.1 25.4 15.7 10.5 100.0 3,184 0.47 South West Highlands 19.4 20.7 24.2 23.9 11.9 100.0 5,769 0.39 Lake 24.0 24.6 22.8 18.1 10.5 100.0 17,264 0.40 Eastern 5.1 9.6 10.0 21.3 53.9 100.0 9,430 0.31 Zanzibar 0.7 6.0 14.1 32.4 46.8 100.0 1,713 0.39 Region Dodoma 30.7 19.3 24.0 22.1 4.0 100.0 2,936 0.26 Arusha 24.2 13.4 16.1 21.0 25.3 100.0 2,102 0.60 Kilimanjaro 2.8 5.8 17.1 42.4 31.9 100.0 1,652 0.32 Tanga 10.8 17.4 20.5 22.3 29.0 100.0 2,825 0.43 Morogoro 12.9 19.4 21.2 27.5 18.9 100.0 2,943 0.45 Pwani 7.3 25.4 24.2 27.3 15.8 100.0 1,332 0.47 Dar es Salaam 0.1 0.0 0.0 16.1 83.8 100.0 5,156 0.08 Lindi 17.8 30.4 26.1 16.5 9.1 100.0 1,304 0.47 Mtwara 18.7 29.9 24.8 15.0 11.5 100.0 1,880 0.54 Ruvuma 14.7 20.5 26.4 24.0 14.5 100.0 1,735 0.47 Iringa 8.2 15.8 25.7 26.2 24.2 100.0 1,210 0.56 Mbeya 13.8 21.0 24.3 26.9 14.0 100.0 3,728 0.56 Singida 34.7 25.1 18.5 12.5 9.3 100.0 1,987 0.51 Tabora 45.8 27.1 10.0 10.0 7.1 100.0 3,642 0.68 Rukwa 28.3 19.7 26.1 18.1 7.8 100.0 1,402 0.38 Kigoma 21.9 28.8 29.3 10.5 9.5 100.0 2,636 0.54 Shinyanga 37.3 21.2 16.0 12.7 12.8 100.0 2,389 0.70 Kagera 11.8 34.8 28.4 18.9 6.1 100.0 3,073 0.55 Mwanza 21.0 21.1 19.8 20.2 17.8 100.0 4,131 0.43 Mara 23.3 16.4 22.5 23.6 14.2 100.0 2,549 0.49 Manyara 37.5 20.5 22.5 14.5 4.9 100.0 1,983 0.32 Njombe 6.9 16.8 27.1 33.4 15.8 100.0 882 0.47 Katavi 32.2 21.0 19.2 19.2 8.3 100.0 638 0.66 Simiyu 36.5 30.2 19.2 10.0 4.0 100.0 2,576 0.39 Geita 19.1 23.5 31.1 21.7 4.6 100.0 2,546 0.41 Kaskazini Unguja 1.1 4.4 21.9 59.3 13.2 100.0 272 0.41 Kusini Unguja 0.2 3.2 16.8 52.0 27.7 100.0 160 0.34 Mjini Magharibi 0.0 0.0 1.7 14.7 83.6 100.0 718 0.20 Kaskazini Pemba 1.9 14.9 26.3 36.9 20.0 100.0 291 0.53 Kusini Pemba 1.2 15.9 24.3 35.6 23.0 100.0 272 0.55 Total 20.0 20.0 20.0 20.0 20.0 100.0 60,950 0.37 36 • Housing Characteristics and Household Population Table 2.7 Hand washing Percentage of households in which the place most often used for washing hands was observed, and among households in which the place for hand washing was observed, percent distribution by availability of water, soap and other cleansing agents, Tanzania DHS-MIS 2015-16 Percentage of households in which place for washing hands was observed1 Number of households Among households where place for hand washing was observed, percentage with: Number of households with place for hand washing observed Background characteristic Soap and water2 Water and cleansing agent3 other than soap only Water only Soap but no water4 No water, no soap, no other cleansing agent Total Residence Urban 85.8 4,141 71.9 0.7 24.3 0.7 2.4 100.0 3,555 Rural 78.2 8,422 52.3 0.2 43.9 0.5 3.2 100.0 6,585 Tanzania Mainland/ Zanzibar Mainland 81.4 12,247 59.0 0.4 37.1 0.6 2.9 100.0 9,966 Urban 86.2 4,053 72.0 0.7 24.3 0.7 2.4 100.0 3,494 Rural 79.0 8,195 52.0 0.2 44.1 0.5 3.2 100.0 6,471 Zanzibar 55.0 316 67.2 0.1 27.4 0.4 4.9 100.0 174 Unguja 65.4 213 65.2 0.0 28.9 0.3 5.6 100.0 140 Pemba 33.4 102 75.8 0.4 21.2 0.4 2.1 100.0 34 Zone Western 87.4 1,010 52.2 0.2 43.9 0.1 3.7 100.0 883 Northern 81.8 1,526 65.3 0.1 30.1 1.7 2.8 100.0 1,248 Central 73.8 1,469 46.2 0.0 52.1 0.5 1.2 100.0 1,084 Southern Highlands 83.1 933 63.9 0.1 34.4 0.4 1.3 100.0 775 Southern 61.6 798 54.2 0.5 39.8 0.2 5.4 100.0 491 South West Highlands 87.9 1,306 48.0 0.6 42.0 0.3 9.2 100.0 1,148 Lake 89.2 2,935 54.2 0.1 44.1 0.4 1.2 100.0 2,617 Eastern 75.7 2,270 80.0 1.3 16.1 0.7 2.0 100.0 1,718 Zanzibar 55.0 316 67.2 0.1 27.4 0.4 4.9 100.0 174 Region Dodoma 83.9 683 40.5 0.0 58.1 0.0 1.4 100.0 573 Arusha 72.3 486 51.4 0.3 36.8 3.6 7.9 100.0 351 Kilimanjaro 79.0 431 75.3 0.0 20.9 2.3 1.6 100.0 340 Tanga 91.4 610 68.0 0.0 31.5 0.2 0.3 100.0 557 Morogoro 60.3 698 80.6 0.8 15.7 0.0 2.9 100.0 421 Pwani 56.1 317 78.3 0.9 16.6 0.4 3.7 100.0 178 Dar es Salaam 89.2 1,255 80.0 1.5 16.2 0.9 1.4 100.0 1,119 Lindi 70.1 313 44.1 0.0 46.9 0.4 8.6 100.0 219 Mtwara 56.1 485 62.3 1.0 34.0 0.0 2.8 100.0 272 Ruvuma 91.0 410 63.7 0.0 36.0 0.2 0.2 100.0 373 Iringa 79.5 301 60.5 0.3 37.7 0.3 1.3 100.0 239 Mbeya 83.3 902 47.6 0.8 47.9 0.1 3.6 100.0 751 Singida 64.6 392 56.3 0.0 43.2 0.3 0.2 100.0 253 Tabora 92.1 539 38.7 0.3 57.6 0.0 3.4 100.0 496 Rukwa 97.7 295 46.9 0.3 25.7 0.7 26.4 100.0 288 Kigoma 82.0 472 69.5 0.0 26.3 0.3 4.0 100.0 387 Shinyanga 85.2 400 41.5 0.0 52.3 0.5 5.7 100.0 341 Kagera 90.7 643 81.6 0.3 16.7 1.0 0.5 100.0 583 Mwanza 86.2 717 39.9 0.0 59.0 0.3 0.8 100.0 618 Mara 97.7 437 68.0 0.0 32.0 0.0 0.0 100.0 427 Manyara 65.4 395 48.9 0.0 47.4 1.9 1.8 100.0 258 Njombe 73.6 222 69.4 0.0 25.9 0.9 3.9 100.0 163 Katavi 99.1 110 53.5 0.0 44.0 0.2 2.3 100.0 109 Simiyu 83.2 348 49.2 0.0 49.4 0.0 1.4 100.0 290 Geita 92.0 390 34.2 0.2 65.3 0.0 0.2 100.0 359 Kaskazini Unguja 59.9 51 62.8 0.0 30.2 0.8 6.2 100.0 31 Kusini Unguja 50.2 32 59.3 0.0 39.3 0.0 1.4 100.0 16 Mjini Magharibi 71.3 130 67.0 0.0 26.7 0.3 6.1 100.0 93 Kaskazini Pemba 30.7 54 87.1 0.0 11.8 0.0 1.1 100.0 16 Kusini Pemba 36.3 49 65.2 0.8 30.0 0.8 3.1 100.0 18 Wealth quintile Lowest 75.6 2,107 38.7 0.0 55.6 0.1 5.5 100.0 1,594 Second 74.8 2,394 45.2 0.3 50.7 0.5 3.3 100.0 1,791 Middle 78.1 2,500 54.3 0.1 42.1 0.6 2.9 100.0 1,951 Fourth 83.4 2,687 66.6 0.3 30.7 0.5 1.9 100.0 2,242 Highest 89.1 2,874 78.8 0.8 17.4 0.9 2.0 100.0 2,561 Total 80.7 12,563 59.2 0.4 37.0 0.6 2.9 100.0 10,139 1 Includes fixed and mobile place 2 Soap includes soap or detergent in bar, liquid, powder, or paste form. This column includes households with soap and water only as well as those that had soap and water and another cleansing agent. 3 Cleansing agents other than soap include locally available materials such as ash, mud, or sand. 4 Includes households with soap only as well as those with soap and another cleansing agent Housing Characteristics and Household Population • 37 Table 2.8 Household population by age, sex, and residence Percent distribution of the de facto household population by 5-year age groups, according to sex and residence, Tanzania DHS-MIS 2015-16 Urban Rural Tanzania Total Age Male Female Total Male Female Total Male Female <5 16.1 13.7 14.8 18.3 17.2 17.7 17.7 16.2 16.9 5-9 13.7 12.0 12.8 17.7 16.4 17.0 16.5 15.1 15.8 10-14 11.5 11.4 11.4 14.6 14.2 14.4 13.7 13.4 13.5 15-19 10.7 12.0 11.4 10.3 8.7 9.5 10.5 9.7 10.1 20-24 9.0 10.8 9.9 6.3 7.1 6.7 7.1 8.2 7.7 25-29 7.3 9.0 8.2 5.5 6.1 5.8 6.0 7.0 6.5 30-34 7.1 7.4 7.3 4.3 5.0 4.7 5.1 5.7 5.4 35-39 6.3 6.5 6.4 4.7 4.9 4.8 5.2 5.4 5.3 40-44 5.1 4.7 4.9 3.8 4.3 4.1 4.2 4.4 4.3 45-49 3.8 3.0 3.4 3.2 3.2 3.2 3.3 3.2 3.2 50-54 2.6 2.8 2.7 2.7 3.4 3.1 2.7 3.2 2.9 55-59 2.1 1.8 1.9 2.2 2.4 2.3 2.2 2.2 2.2 60-64 1.9 1.8 1.8 2.0 1.9 1.9 1.9 1.9 1.9 65-69 1.3 1.1 1.2 1.4 1.3 1.3 1.4 1.2 1.3 70-74 0.7 0.9 0.8 1.1 1.4 1.3 1.0 1.2 1.1 75-79 0.4 0.4 0.4 0.7 1.1 0.9 0.7 0.9 0.8 80 + 0.3 0.7 0.5 1.2 1.4 1.3 0.9 1.2 1.1 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Dependency age groups 0-14 41.3 37.1 39.1 50.6 47.8 49.1 47.9 44.6 46.2 15-64 56.0 59.8 58.0 45.0 47.1 46.1 48.1 50.9 49.6 65+ 2.7 3.1 2.9 4.5 5.1 4.8 4.0 4.5 4.2 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Child and adult populations 0-17 48.0 44.1 45.9 57.4 52.9 55.1 54.7 50.3 52.4 18+ 52.0 55.9 54.1 42.6 47.1 44.9 45.3 49.7 47.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Number of persons 8,307 9,140 17,447 20,446 21,764 42,210 28,753 30,904 59,657 Table 2.9 Household composition Percent distribution of households by sex of head of household and by household size; mean size of household, and percentage of households with orphans and foster children under age 18, according to residence, Tanzania DHS-MIS 2015-16 Tanzania Mainland Zanzibar Tanzania Characteristic Urban Rural Total Household headship Male 74.4 76.0 75.5 77.9 75.5 Female 25.6 24.0 24.5 22.1 24.5 Total 100.0 100.0 100.0 100.0 100.0 Number of usual members 1 13.5 7.9 9.7 5.7 9.6 2 13.0 10.3 11.2 8.3 11.1 3 16.1 13.9 14.7 13.8 14.6 4 16.4 14.7 15.3 14.0 15.2 5 14.6 14.9 14.8 12.4 14.7 6 9.4 12.3 11.3 12.5 11.4 7 6.6 8.9 8.2 11.4 8.3 8 4.7 6.6 5.9 8.2 6.0 9+ 5.7 10.5 8.9 13.6 9.0 Total 100.0 100.0 100.0 100.0 100.0 Mean size of households 4.3 5.1 4.8 5.4 4.9 Percentage of households with orphans and foster children under age 18 Double orphans 1.8 1.5 1.6 0.4 1.6 Single orphans1 10.5 11.7 11.3 8.9 11.2 Foster children2 25.9 27.2 26.8 29.5 26.8 Foster and/or orphan children 29.0 31.2 30.5 32.7 30.6 Number of households 4,053 8,195 12,247 316 12,563 Note: Table is based on de jure household members, i.e., usual residents. 1 Includes children with one dead parent and an unknown survival status of the other parent. 2 Foster children are those under age 18 living in households with neither their mother nor their father present, and the mother and/or the father are alive. 38 • H ou si ng C ha ra ct er is tic s an d H ou se ho ld P op ul at io n Ta bl e 2. 10 C hi ld re n’ s liv in g ar ra ng em en ts a nd o rp ha nh oo d P er ce nt d is tri bu tio n of d e ju re c hi ld re n un de r ag e 18 b y liv in g ar ra ng em en ts a nd s ur vi va l s ta tu s of p ar en ts , t he p er ce nt ag e of c hi ld re n no t l iv in g w ith a b io lo gi ca l p ar en t, an d th e pe rc en ta ge o f c hi ld re n w ith o ne o r bo th p ar en ts de ad , a cc or di ng to b ac kg ro un d ch ar ac te ris tic s, T an za ni a D H S -M IS 2 01 5- 16 Li vi ng w ith bo th p ar en ts Li vi ng w ith m ot he r b ut no t w ith fa th er Li vi ng w ith fa th er b ut no t w ith m ot he r N ot li vi ng w ith e ith er p ar en t To ta l P er ce nt ag e no t l iv in g w ith a bi ol og ic al pa re nt P er ce nt ag e w ith o ne o r bo th p ar en ts de ad 1 N um be r o f ch ild re n B ac kg ro un d ch ar ac te ris tic Fa th er al iv e Fa th er de ad M ot he r al iv e M ot he r de ad B ot h al iv e O nl y fa th er al iv e O nl y m ot he r al iv e B ot h de ad M is si ng in fo rm at io n on fa th er / m ot he r A ge 0- 4 70 .6 18 .3 1. 4 1. 6 0. 1 6. 8 0. 5 0. 4 0. 1 0. 3 10 0. 0 7. 7 2. 5 10 ,0 90 <2 75 .2 21 .7 1. 1 0. 3 0. 0 1. 4 0. 1 0. 0 0. 0 0. 2 10 0. 0 1. 6 1. 3 4, 16 6 2- 4 67 .4 15 .9 1. 6 2. 6 0. 2 10 .5 0. 8 0. 6 0. 1 0. 3 10 0. 0 12 .0 3. 4 5, 92 4 5- 9 58 .8 13 .7 3. 1 5. 2 0. 5 14 .7 1. 2 1. 6 0. 6 0. 6 10 0. 0 18 .1 7. 2 9, 50 4 10 -1 4 51 .4 12 .0 5. 3 6. 5 1. 1 17 .0 2. 0 2. 9 1. 2 0. 5 10 0. 0 23 .1 12 .6 8, 22 0 15 -1 7 41 .9 10 .2 6. 8 6. 0 1. 6 23 .2 2. 7 4. 4 2. 2 1. 0 10 0. 0 32 .5 17 .9 3, 74 1 S ex M al e 59 .6 14 .0 3. 7 4. 9 0. 7 12 .5 1. 3 1. 9 0. 9 0. 5 10 0. 0 16 .6 8. 6 15 ,8 83 Fe m al e 57 .7 14 .5 3. 5 4. 1 0. 6 15 .0 1. 4 1. 9 0. 7 0. 5 10 0. 0 19 .0 8. 2 15 ,6 72 R es id en ce U rb an 53 .2 16 .7 3. 2 4. 7 0. 7 16 .1 1. 8 2. 0 1. 0 0. 6 10 0. 0 20 .9 8. 8 8, 11 5 R ur al 60 .5 13 .4 3. 7 4. 4 0. 7 12 .9 1. 2 1. 8 0. 7 0. 5 10 0. 0 16 .7 8. 2 23 ,4 40 Ta nz an ia M ai nl an d/ Za nz ib ar M ai nl an d 58 .5 14 .4 3. 6 4. 5 0. 7 13 .7 1. 4 1. 9 0. 8 0. 5 10 0. 0 17 .8 8. 4 30 ,7 17 U rb an 52 .9 16 .9 3. 2 4. 7 0. 7 16 .2 1. 8 2. 0 1. 1 0. 6 10 0. 0 21 .0 8. 9 7, 88 5 R ur al 60 .4 13 .5 3. 8 4. 5 0. 7 12 .9 1. 2 1. 8 0. 7 0. 5 10 0. 0 16 .7 8. 3 22 ,8 32 Za nz ib ar 65 .6 10 .9 2. 6 2. 9 0. 5 14 .8 1. 0 1. 2 0. 1 0. 4 10 0. 0 17 .1 5. 5 83 8 U ng uj a 61 .7 11 .9 2. 7 3. 7 0. 6 16 .6 0. 9 1. 3 0. 2 0. 5 10 0. 0 19 .0 5. 8 53 2 P em ba 72 .5 9. 2 2. 4 1. 6 0. 3 11 .6 1. 2 1. 0 0. 0 0. 2 10 0. 0 13 .8 4. 9 30 6 Zo ne W es te rn 68 .1 9. 7 3. 4 4. 8 0. 3 10 .5 1. 0 1. 6 0. 5 0. 2 10 0. 0 13 .5 6. 8 3, 59 9 N or th er n 57 .5 15 .7 3. 0 3. 3 0. 7 15 .6 1. 5 1. 4 0. 9 0. 6 10 0. 0 19 .3 7. 6 3, 10 5 C en tra l 60 .4 15 .3 4. 0 3. 2 0. 5 13 .1 1. 2 1. 2 0. 5 0. 5 10 0. 0 16 .0 7. 5 3, 67 3 S ou th er n H ig hl an ds 53 .5 17 .3 5. 0 4. 9 1. 2 11 .8 1. 5 2. 5 1. 5 1. 0 10 0. 0 17 .3 11 .8 1, 87 1 S ou th er n 42 .5 24 .8 3. 6 7. 0 0. 6 17 .9 0. 9 1. 5 0. 6 0. 5 10 0. 0 20 .9 7. 3 1, 45 4 S ou th W es t H ig hl an ds 60 .6 13 .3 3. 5 3. 1 0. 6 14 .1 1. 0 2. 1 1. 3 0. 4 10 0. 0 18 .5 8. 5 3, 08 9 La ke 57 .3 13 .6 3. 6 5. 3 0. 9 14 .1 1. 5 2. 3 0. 9 0. 5 10 0. 0 18 .7 9. 3 9, 78 2 E as te rn 58 .1 14 .3 3. 4 4. 6 0. 4 14 .1 2. 0 1. 8 0. 4 0. 8 10 0. 0 18 .3 8. 1 4, 14 4 Za nz ib ar 65 .6 10 .9 2. 6 2. 9 0. 5 14 .8 1. 0 1. 2 0. 1 0. 4 10 0. 0 17 .1 5. 5 83 8 (C on tin ue d… ) H ou si ng C ha ra ct er is tic s an d H ou se ho ld P op ul at io n • 3 9 Ta bl e 2. 10 — C on tin ue d Li vi ng w ith bo th p ar en ts Li vi ng w ith m ot he r b ut no t w ith fa th er Li vi ng w ith fa th er b ut no t w ith m ot he r N ot li vi ng w ith e ith er p ar en t To ta l P er ce nt ag e no t l iv in g w ith a bi ol og ic al pa re nt P er ce nt ag e w ith o ne o r bo th p ar en ts de ad 1 N um be r o f ch ild re n B ac kg ro un d ch ar ac te ris tic Fa th er al iv e Fa th er de ad M ot he r al iv e M ot he r de ad B ot h al iv e O nl y fa th er al iv e O nl y m ot he r al iv e B ot h de ad M is si ng in fo rm at io n on fa th er / m ot he r R eg io n D od om a 55 .0 16 .3 5. 5 3. 4 0. 2 16 .0 1. 1 1. 7 0. 3 0. 5 10 0. 0 19 .1 8. 9 1, 55 9 A ru sh a 65 .9 12 .5 2. 9 3. 1 0. 9 11 .7 0. 9 0. 8 1. 2 0. 2 10 0. 0 14 .5 6. 6 1, 05 1 K ili m an ja ro 55 .5 12 .3 3. 6 2. 7 0. 6 19 .6 1. 4 2. 4 0. 3 1. 6 10 0. 0 23 .7 8. 7 70 7 Ta ng a 51 .9 19 .9 2. 9 3. 7 0. 5 16 .4 2. 1 1. 4 0. 9 0. 3 10 0. 0 20 .8 7. 8 1, 34 7 M or og or o 55 .8 15 .5 4. 7 4. 2 0. 6 14 .6 2. 2 1. 1 0. 2 1. 1 10 0. 0 18 .1 8. 9 1, 43 8 P w an i 54 .7 17 .4 2. 6 5. 5 0. 3 15 .1 1. 0 2. 4 0. 2 0. 7 10 0. 0 18 .7 6. 7 64 5 D ar e s S al aa m 60 .8 12 .6 2. 8 4. 7 0. 3 13 .5 2. 1 2. 1 0. 6 0. 6 10 0. 0 18 .3 8. 0 2, 06 1 Li nd i 47 .1 22 .2 4. 1 5. 5 0. 3 16 .3 1. 2 1. 6 1. 0 0. 7 10 0. 0 20 .1 8. 1 63 0 M tw ar a 39 .0 26 .8 3. 3 8. 1 0. 8 19 .1 0. 7 1. 4 0. 4 0. 4 10 0. 0 21 .6 6. 7 82 4 R uv um a 53 .8 16 .2 4. 7 6. 4 1. 2 10 .8 2. 2 2. 7 0. 7 1. 3 10 0. 0 16 .3 11 .5 86 0 Iri ng a 49 .9 18 .4 5. 2 3. 6 1. 3 14 .7 1. 1 2. 6 2. 5 0. 6 10 0. 0 20 .9 12 .8 58 6 M be ya 56 .6 12 .5 3. 9 3. 4 0. 8 17 .4 1. 1 2. 2 1. 6 0. 5 10 0. 0 22 .3 9. 5 1, 91 3 S in gi da 63 .5 11 .9 2. 6 3. 9 1. 0 12 .6 1. 4 1. 2 1. 3 0. 5 10 0. 0 16 .5 7. 5 1, 05 2 Ta bo ra 64 .6 9. 4 3. 0 6. 3 0. 5 12 .3 1. 2 1. 9 0. 7 0. 2 10 0. 0 16 .0 7. 2 2, 11 6 R uk w a 67 .7 16 .5 2. 8 1. 6 0. 3 7. 5 0. 6 2. 1 0. 6 0. 3 10 0. 0 10 .7 6. 3 80 5 K ig om a 73 .0 10 .1 4. 0 2. 6 0. 1 7. 9 0. 6 1. 2 0. 3 0. 1 10 0. 0 10 .0 6. 2 1, 48 3 S hi ny an ga 60 .9 11 .2 3. 8 5. 4 0. 3 13 .8 1. 0 1. 9 1. 3 0. 4 10 0. 0 17 .9 8. 4 1, 32 4 K ag er a 66 .1 11 .2 3. 5 4. 3 0. 8 9. 1 2. 1 2. 0 0. 3 0. 6 10 0. 0 13 .5 8. 8 1, 70 3 M w an za 46 .3 19 .2 2. 4 6. 1 1. 1 18 .6 1. 9 2. 7 1. 1 0. 5 10 0. 0 24 .3 9. 4 2, 27 1 M ar a 56 .1 13 .0 6. 1 3. 5 0. 5 15 .4 1. 5 2. 3 1. 1 0. 5 10 0. 0 20 .3 11 .6 1, 46 2 M an ya ra 65 .4 17 .2 3. 0 2. 3 0. 6 9. 4 1. 1 0. 6 0. 1 0. 4 10 0. 0 11 .1 5. 3 1, 06 3 N jo m be 57 .7 17 .9 5. 0 3. 5 0. 9 9. 7 0. 9 1. 9 1. 7 0. 8 10 0. 0 14 .1 10 .7 42 5 K at av i 66 .2 10 .3 2. 9 4. 7 0. 4 10 .9 1. 7 1. 5 1. 1 0. 2 10 0. 0 15 .3 7. 7 37 2 S im iy u 59 .7 12 .4 2. 6 4. 8 1. 4 14 .1 1. 2 2. 3 0. 8 0. 7 10 0. 0 18 .3 8. 2 1, 51 9 G ei ta 59 .2 11 .5 4. 0 7. 6 1. 4 11 .8 0. 7 2. 6 0. 7 0. 4 10 0. 0 15 .8 9. 7 1, 50 4 K as ka zi ni U ng uj a 72 .4 5. 2 2. 3 4. 3 0. 9 12 .5 0. 4 1. 6 0. 2 0. 2 10 0. 0 14 .8 5. 4 13 8 K us in i U ng uj a 55 .0 13 .8 2. 8 3. 2 0. 2 21 .4 0. 6 1. 3 0. 2 1. 5 10 0. 0 23 .5 5. 1 80 M jin i M ag ha rib i 58 .6 14 .4 2. 9 3. 5 0. 6 17 .1 1. 2 1. 2 0. 2 0. 3 10 0. 0 19 .7 6. 1 31 4 K as ka zi ni P em ba 74 .2 7. 9 2. 7 1. 6 0. 2 10 .6 1. 7 1. 1 0. 0 0. 0 10 0. 0 13 .4 5. 7 15 9 K us in i P em ba 70 .7 10 .6 2. 1 1. 5 0. 5 12 .7 0. 5 1. 0 0. 0 0. 4 10 0. 0 14 .2 4. 1 14 7 W ea lth q ui nt ile Lo w es t 62 .5 13 .2 4. 6 4. 2 0. 3 11 .2 1. 1 1. 9 0. 6 0. 4 10 0. 0 14 .8 8. 6 7, 09 5 S ec on d 59 .7 15 .5 4. 0 3. 7 0. 7 12 .4 1. 2 1. 5 0. 9 0. 4 10 0. 0 16 .0 8. 4 6, 76 3 M id dl e 59 .7 13 .1 3. 4 4. 3 0. 9 14 .0 1. 3 1. 9 0. 6 0. 7 10 0. 0 17 .9 8. 2 6, 48 1 Fo ur th 55 .4 15 .3 3. 2 5. 7 1. 0 14 .5 1. 7 1. 9 0. 8 0. 5 10 0. 0 18 .9 8. 7 6, 09 5 H ig he st 54 .4 14 .5 2. 3 4. 8 0. 4 17 .9 1. 7 2. 1 1. 0 0. 8 10 0. 0 22 .7 7. 7 5, 12 0 To ta l < 15 60 .9 14 .8 3. 2 4. 3 0. 6 12 .5 1. 2 1. 5 0. 6 0. 5 10 0. 0 15 .8 7. 1 27 ,8 14 To ta l < 18 58 .6 14 .3 3. 6 4. 5 0. 7 13 .8 1. 4 1. 9 0. 8 0. 5 10 0. 0 17 .8 8. 4 31 ,5 55 N ot e: T ab le is b as ed o n de ju re m em be rs , i .e ., us ua l r es id en ts . 1 In cl ud es c hi ld re n w ith fa th er d ea d, m ot he r d ea d, b ot h de ad a nd o ne p ar en t d ea d bu t m is si ng in fo rm at io n on s ur vi va l s ta tu s of th e ot he r p ar en t. 40 • Housing Characteristics and Household Population Table 2.11 Birth registration of children under age 5 Percentage of de jure children under age 5 whose births are registered with the civil authorities, according to background characteristics, Tanzania DHS-MIS 2015-16 Children whose births are registered Number of children Background characteristic Percentage who had birth certificate Percentage who did not have birth certificate Percentage registered Age <2 11.0 15.1 26.0 4,166 2-4 16.2 10.4 26.7 5,924 Sex Male 14.6 13.2 27.8 5,061 Female 13.5 11.5 25.0 5,029 Residence Urban 29.5 21.4 50.9 2,642 Rural 8.6 9.1 17.7 7,449 Tanzania Mainland/Zanzibar Mainland 12.7 11.9 24.6 9,828 Urban 28.1 21.5 49.6 2,566 Rural 7.3 8.5 15.8 7,262 Zanzibar 63.6 28.1 91.7 262 Unguja 72.3 22.9 95.2 166 Pemba 48.6 37.0 85.6 96 Zone Western 5.6 7.3 12.8 1,210 Northern 18.4 22.9 41.2 957 Central 5.0 9.5 14.5 1,113 Southern Highlands 6.5 7.7 14.2 561 Southern 9.3 14.9 24.2 407 South West Highlands 21.8 4.4 26.2 976 Lake 10.6 6.0 16.6 3,260 Eastern 23.6 31.0 54.7 1,343 Zanzibar 63.6 28.1 91.7 262 Region Dodoma 6.1 4.9 11.0 436 Arusha 22.6 15.5 38.2 353 Kilimanjaro 24.3 43.2 67.5 185 Tanga 12.2 20.0 32.2 419 Morogoro 6.2 23.6 29.8 431 Pwani 11.2 31.4 42.5 202 Dar es Salaam 37.7 35.5 73.2 710 Lindi 7.8 9.7 17.5 192 Mtwara 10.6 19.5 30.2 216 Ruvuma 5.2 2.7 7.9 264 Iringa 8.4 13.4 21.8 174 Mbeya 35.6 6.2 41.8 563 Singida 4.5 12.1 16.6 335 Tabora 5.3 3.4 8.7 688 Rukwa 3.7 1.8 5.5 279 Kigoma 6.0 12.3 18.3 522 Shinyanga 4.0 4.1 8.1 456 Kagera 2.1 8.2 10.3 546 Mwanza 31.9 7.1 39.0 791 Mara 7.0 4.9 11.8 497 Manyara 4.2 12.8 16.9 341 Njombe 6.7 10.3 17.0 123 Katavi 1.6 2.3 3.9 134 Simiyu 1.9 2.1 4.1 502 Geita 4.4 8.7 13.1 468 Kaskazini Unguja 64.1 28.7 92.8 44 Kusini Unguja 77.4 16.2 93.6 26 Mjini Magharibi 74.7 22.0 96.7 97 Kaskazini Pemba 46.3 41.0 87.3 50 Kusini Pemba 51.0 32.8 83.8 46 Wealth quintile Lowest 3.1 4.6 7.7 2,462 Second 7.1 8.1 15.2 2,169 Middle 8.8 11.3 20.0 1,969 Fourth 18.4 18.8 37.2 1,865 Highest 41.3 23.8 65.1 1,626 Total 14.0 12.3 26.4 10,090 Housing Characteristics and Household Population • 41 Table 2.12 School attendance by survivorship of parents For de jure children age 10-14, the percentage attending school by parental survival and the ratio of the percentage attending, by parental survival, according to background characteristics, Tanzania DHS-MIS 2015-16 Percentage attending school by survivorship of parents Background characteristic Both parents deceased Number of children Both parents alive and living with at least one parent Number of children Ratio1 Sex Male 70.5 65 83.4 2,857 0.85 Female (79.0) 34 84.8 2,890 (0.93) Residence Urban (78.9) 29 93.0 1,326 (0.85) Rural 71.1 69 81.5 4,421 0.87 Tanzania Mainland/Zanzibar Mainland 73.7 98 83.8 5,586 0.88 Urban (78.9) 29 92.8 1,283 (0.85) Rural 71.4 69 81.2 4,303 0.88 Zanzibar * 0 93.3 161 na Unguja * 0 96.8 97 na Pemba * 0 88.1 64 na Total 73.4 99 84.1 5,747 0.87 Notes: Table is based on children who usually live in the household, that is, de jure residents. Figures in parentheses are based on 25-49 unweighted cases. An asterisk indicates that a figure is based on fewer than 25 unweighted cases and has been suppressed. na = Not applicable 1 Ratio of the percentages attending school for children with both parents deceased to the percentages attending school with both parents alive and living with at least one parent 42 • Housing Characteristics and Household Population Table 2.13.1 Educational attainment of the female household population Percent distribution of the de facto female household population age six and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Tanzania DHS-MIS 2015-16 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Total Number Median years completed Age 6-9 44.1 55.9 0.0 0.0 0.0 0.0 100.0 3,764 0.0 10-14 9.0 77.0 10.0 4.0 0.0 0.0 100.0 4,140 3.3 15-19 6.3 14.4 43.7 26.7 8.8 0.0 100.0 2,993 6.6 20-24 10.1 9.4 43.6 9.8 25.6 1.4 100.0 2,534 6.7 25-29 16.8 10.6 48.9 4.9 15.9 2.9 100.0 2,159 6.5 30-34 20.8 12.7 52.4 2.6 9.5 2.0 100.0 1,772 6.3 35-39 20.3 10.5 56.9 3.2 7.9 1.2 100.0 1,665 6.3 40-44 22.0 10.9 57.7 2.3 5.8 1.4 100.0 1,370 6.3 45-49 18.9 10.2 60.7 2.9 5.7 1.6 100.0 975 6.4 50-54 33.1 15.0 46.5 1.4 3.7 0.3 100.0 988 6.0 55-59 45.4 20.4 27.4 1.3 5.3 0.3 100.0 680 1.7 60-64 54.7 28.6 13.0 1.0 2.4 0.3 100.0 583 0.0 65+ 75.9 18.6 3.9 0.1 0.9 0.6 100.0 1,391 0.0 Residence Urban 12.1 25.8 34.9 9.6 15.3 2.3 100.0 7,700 6.3 Rural 29.5 32.2 30.2 4.4 3.6 0.1 100.0 17,314 3.2 Tanzania Mainland/ Zanzibar Mainland 24.2 30.3 32.3 5.5 6.9 0.8 100.0 24,298 4.4 Urban 12.0 25.9 35.7 9.1 15.0 2.3 100.0 7,482 6.3 Rural 29.7 32.2 30.8 3.8 3.3 0.1 100.0 16,816 3.2 Zanzibar 21.4 27.9 9.2 25.2 15.1 1.1 100.0 716 6.1 Unguja 15.0 26.3 10.3 28.3 18.6 1.5 100.0 487 6.8 Pemba 35.1 31.3 6.9 18.8 7.9 0.1 100.0 229 2.5 Zone Western 34.8 30.0 27.9 3.4 3.8 0.2 100.0 2,495 2.3 Northern 18.7 29.3 33.6 7.0 10.7 0.7 100.0 2,874 6.1 Central 29.8 28.8 32.4 4.1 4.7 0.1 100.0 2,788 3.6 Southern Highlands 17.7 30.3 37.9 6.7 6.8 0.5 100.0 1,569 6.1 Southern 28.2 29.6 34.5 4.0 3.3 0.4 100.0 1,384 3.8 South West Highlands 23.2 32.1 33.3 5.6 4.9 0.9 100.0 2,394 4.2 Lake 26.7 34.8 28.9 4.8 4.5 0.4 100.0 6,813 3.3 Eastern 15.3 23.6 36.4 7.8 14.3 2.7 100.0 3,982 6.3 Zanzibar 21.4 27.9 9.2 25.2 15.1 1.1 100.0 716 6.1 Region Dodoma 30.7 30.0 32.1 2.9 4.3 0.0 100.0 1,186 3.1 Arusha 23.3 25.8 32.4 6.4 10.7 1.4 100.0 872 6.0 Kilimanjaro 7.2 36.1 34.6 10.5 10.8 0.6 100.0 766 6.2 Tanga 22.5 27.5 33.9 5.2 10.7 0.2 100.0 1,236 6.0 Morogoro 23.3 29.4 35.1 5.6 6.5 0.2 100.0 1,214 4.8 Pwani 31.8 26.5 30.6 4.7 5.4 1.0 100.0 556 3.3 Dar es Salaam 6.8 19.6 38.6 9.8 20.8 4.4 100.0 2,212 6.6 Lindi 28.2 31.0 32.8 3.6 3.7 0.6 100.0 534 3.7 Mtwara 28.2 28.7 35.5 4.3 3.0 0.3 100.0 850 3.8 Ruvuma 15.3 32.7 40.8 5.4 5.7 0.1 100.0 689 6.0 Iringa 22.1 27.4 31.3 8.7 9.3 1.1 100.0 498 6.0 Mbeya 19.1 30.1 36.9 6.9 5.7 1.2 100.0 1,592 6.0 Singida 28.4 27.0 34.9 4.3 5.4 0.1 100.0 812 4.3 Tabora 37.8 29.4 25.9 3.2 3.5 0.2 100.0 1,462 2.0 Rukwa 28.5 37.4 26.9 3.0 4.0 0.3 100.0 563 2.3 Kigoma 30.6 30.8 30.7 3.5 4.2 0.2 100.0 1,032 2.7 Shinyanga 30.6 31.5 29.4 3.1 5.2 0.3 100.0 944 3.2 Kagera 25.3 36.9 30.3 3.5 4.0 0.0 100.0 1,246 3.4 Mwanza 24.2 34.5 28.2 6.0 6.2 1.0 100.0 1,629 3.8 Mara 21.4 36.7 30.5 6.5 4.6 0.3 100.0 1,059 3.8 Manyara 29.9 28.9 30.4 5.8 4.7 0.4 100.0 790 3.8 Njombe 16.2 29.9 41.4 6.5 5.6 0.4 100.0 382 6.1 Katavi 38.0 32.3 24.2 3.4 2.0 0.1 100.0 240 1.8 Simiyu 29.9 30.6 30.2 5.8 3.4 0.0 100.0 982 3.4 Geita 31.5 37.7 24.7 3.1 2.8 0.3 100.0 953 2.2 Kaskazini Unguja 26.0 35.4 7.8 23.7 7.1 0.0 100.0 104 3.8 Kusini Unguja 15.9 31.3 10.2 31.1 11.0 0.4 100.0 67 6.3 Mjini Magharibi 11.2 22.2 11.2 29.2 23.9 2.3 100.0 316 8.0 Kaskazini Pemba 38.1 33.0 5.4 17.7 5.7 0.1 100.0 120 1.6 Kusini Pemba 31.8 29.4 8.5 19.9 10.2 0.2 100.0 110 3.5 Wealth quintile Lowest 42.5 30.5 24.5 1.6 0.8 0.0 100.0 4,721 0.8 Second 34.0 32.6 29.6 2.6 1.1 0.0 100.0 4,897 2.2 Middle 25.4 34.5 33.4 4.5 2.3 0.0 100.0 4,895 3.6 Fourth 15.0 32.1 35.8 9.0 7.9 0.2 100.0 5,081 6.1 Highest 6.7 22.1 34.3 11.6 21.8 3.5 100.0 5,420 6.6 Total 24.1 30.2 31.7 6.0 7.2 0.8 100.0 25,014 4.5 1 Completed at least grade 7 at the primary level 2 Completed grade 4 at the secondary level Housing Characteristics and Household Population • 43 Table 2.13.2 Educational attainment of the male household population Percent distribution of the de facto male household population age six and over by highest level of schooling attended or completed and median years completed, according to background characteristics, Tanzania DHS-MIS 2015-16 Background characteristic No education Some primary Completed primary1 Some secondary Completed secondary2 More than secondary Total Number Median years completed Age 6-9 53.0 46.9 0.0 0.0 0.0 0.0 100.0 3,861 0.0 10-14 10.5 79.4 7.4 2.7 0.0 0.0 100.0 3,936 2.7 15-19 8.3 24.3 37.8 23.7 5.8 0.0 100.0 3,006 6.4 20-24 6.8 11.9 39.7 12.2 27.3 2.0 100.0 2,031 6.8 25-29 10.1 13.5 43.1 7.3 21.2 4.8 100.0 1,722 6.6 30-34 10.5 12.3 53.4 6.6 12.9 4.3 100.0 1,473 6.5 35-39 12.3 13.7 57.0 3.7 9.9 3.4 100.0 1,489 6.4 40-44 10.6 11.7 62.6 2.7 9.6 2.9 100.0 1,212 6.5 45-49 10.3 8.4 66.5 1.9 9.4 3.5 100.0 962 6.5 50-54 12.0 12.3 62.8 1.9 8.1 2.9 100.0 770 6.4 55-59 13.5 19.1 50.3 1.9 10.3 4.8 100.0 622 6.4 60-64 27.1 25.2 31.7 2.1 11.6 2.3 100.0 555 3.9 65+ 37.6 38.8 18.2 0.6 3.7 1.0 100.0 1,140 3.1 Residence Urban 8.5 27.0 31.2 10.9 17.7 4.7 100.0 6,753 6.5 Rural 23.5 35.7 31.7 4.4 4.2 0.4 100.0 16,027 3.7 Tanzania Mainland/ Zanzibar Mainland 19.1 33.1 32.2 5.8 8.1 1.7 100.0 22,173 5.0 Urban 8.5 27.0 31.8 10.4 17.6 4.6 100.0 6,573 6.5 Rural 23.6 35.7 32.3 3.9 4.1 0.4 100.0 15,600 3.7 Zanzibar 16.4 33.9 9.6 24.1 13.3 2.7 100.0 606 5.9 Unguja 11.1 33.1 9.8 27.0 15.6 3.5 100.0 413 6.6 Pemba 27.9 35.7 9.2 18.0 8.4 0.8 100.0 194 3.1 Zone Western 29.8 36.3 25.3 3.8 4.2 0.6 100.0 2,276 2.6 Northern 15.5 30.4 34.7 7.0 11.0 1.4 100.0 2,565 6.1 Central 23.9 33.3 32.7 4.2 5.2 0.6 100.0 2,636 3.7 Southern Highlands 13.5 32.8 38.9 5.5 8.3 0.9 100.0 1,512 6.1 Southern 19.6 32.0 38.1 4.0 5.6 0.8 100.0 1,194 5.3 South West Highlands 17.5 35.7 32.1 5.9 6.7 2.2 100.0 2,114 4.7 Lake 21.0 36.7 29.7 5.9 6.0 0.8 100.0 6,296 3.9 Eastern 11.5 25.5 33.9 8.2 15.8 5.1 100.0 3,581 6.4 Zanzibar 16.4 33.9 9.6 24.1 13.3 2.7 100.0 606 5.9 Region Dodoma 24.6 36.1 30.2 4.4 4.4 0.3 100.0 1,171 3.1 Arusha 17.6 29.0 33.4 5.5 13.0 1.5 100.0 797 6.1 Kilimanjaro 5.9 32.1 39.4 8.9 10.7 3.0 100.0 661 6.3 Tanga 19.7 30.4 32.9 6.8 9.7 0.4 100.0 1,107 5.9 Morogoro 18.7 32.2 37.2 4.6 6.2 1.1 100.0 1,118 5.5 Pwani 21.7 30.4 32.8 6.0 7.8 1.3 100.0 480 5.3 Dar es Salaam 5.0 20.5 32.3 10.8 23.2 8.2 100.0 1,983 6.8 Lindi 23.0 31.8 34.3 4.9 5.0 1.0 100.0 468 4.5 Mtwara 17.4 32.1 40.5 3.3 6.0 0.7 100.0 726 6.0 Ruvuma 12.9 35.2 41.1 4.6 5.6 0.5 100.0 685 6.0 Iringa 14.9 29.6 33.4 6.9 13.6 1.7 100.0 481 6.2 Mbeya 12.5 35.4 34.9 6.9 7.6 2.7 100.0 1,394 6.1 Singida 19.9 32.0 37.0 4.8 5.4 0.9 100.0 734 5.2 Tabora 32.7 34.7 26.2 3.1 3.2 0.1 100.0 1,354 2.4 Rukwa 25.6 35.9 27.8 3.5 5.9 1.2 100.0 483 3.1 Kigoma 25.4 38.6 24.1 4.9 5.6 1.4 100.0 922 2.9 Shinyanga 25.8 32.7 30.0 4.8 6.0 0.8 100.0 870 3.8 Kagera 19.9 38.5 32.2 4.7 4.6 0.1 100.0 1,151 4.1 Mwanza 18.5 35.6 27.3 7.9 9.5 1.2 100.0 1,495 4.3 Mara 15.5 37.7 34.1 5.7 5.2 1.6 100.0 861 4.7 Manyara 26.9 30.3 32.4 3.3 6.4 0.9 100.0 732 3.7 Njombe 12.9 32.6 42.3 5.0 6.3 0.9 100.0 346 6.1 Katavi 29.9 36.9 24.2 4.8 3.4 0.7 100.0 236 2.7 Simiyu 26.0 34.7 29.4 4.9 4.5 0.3 100.0 933 3.3 Geita 21.7 41.0 26.3 6.2 4.3 0.4 100.0 986 3.4 Kaskazini Unguja 17.9 46.3 9.4 19.4 6.7 0.4 100.0 101 4.2 Kusini Unguja 13.5 33.2 12.6 28.9 11.3 0.4 100.0 55 6.3 Mjini Magharibi 7.9 27.8 9.3 29.6 20.0 5.5 100.0 257 8.0 Kaskazini Pemba 29.0 36.4 8.5 17.2 7.9 1.0 100.0 101 2.8 Kusini Pemba 26.7 35.0 10.0 18.8 9.1 0.5 100.0 93 3.5 Wealth quintile Lowest 36.0 34.8 25.7 2.3 1.3 0.0 100.0 4,401 1.7 Second 27.9 37.6 29.6 3.0 1.8 0.0 100.0 4,366 2.8 Middle 17.8 37.7 36.1 4.5 3.9 0.0 100.0 4,690 4.3 Fourth 10.8 33.7 36.7 9.1 9.1 0.6 100.0 4,578 6.2 Highest 4.6 22.5 29.4 12.3 23.8 7.4 100.0 4,745 6.8 Total 19.1 33.1 31.6 6.3 8.2 1.7 100.0 22,780 5.1 1 Completed at least grade 7 at the primary level 2 Completed grade 4 at the secondary level 44 • Housing Characteristics and Household Population Table 2.14 School attendance ratios Net attendance ratios (NARs) and gross attendance ratios (GARs) for the de facto household population by sex and level of schooling; and the Gender Parity Index (GPI), according to background characteristics, Tanzania DHS-MIS 2015-16 Net attendance ratio1 Gross attendance ratio2 Background characteristic Male Female Total Gender Parity Index3 Male Female Total Gender Parity Index3 PRIMARY SCHOOL Residence Urban 84.8 86.6 85.7 1.02 102.5 102.6 102.5 1.00 Rural 69.1 75.7 72.4 1.09 84.8 87.7 86.3 1.04 Region Dodoma 73.2 82.9 77.8 1.13 85.8 93.5 89.4 1.09 Arusha 77.9 80.3 79.1 1.03 92.7 91.0 91.8 0.98 Kilimanjaro 89.9 92.9 91.5 1.03 101.0 109.6 105.6 1.08 Tanga 72.0 82.9 77.3 1.15 88.4 100.8 94.5 1.14 Morogoro 70.1 79.4 74.7 1.13 83.6 94.1 88.8 1.12 Pwani 77.7 81.3 79.6 1.05 96.9 94.2 95.5 0.97 Dar es Salaam 91.3 85.8 88.5 0.94 110.3 99.0 104.4 0.90 Lindi 67.9 79.6 74.0 1.17 80.1 90.7 85.6 1.13 Mtwara 70.7 77.1 74.0 1.09 80.8 85.8 83.3 1.06 Ruvuma 75.9 88.8 81.9 1.17 90.7 101.4 95.7 1.12 Iringa 82.8 86.5 84.6 1.05 97.6 96.3 97.0 0.99 Mbeya 78.5 84.8 81.8 1.08 92.1 97.5 94.9 1.06 Singida 72.6 71.0 71.8 0.98 83.0 82.7 82.8 1.00 Tabora 57.9 62.8 60.4 1.08 69.9 75.4 72.6 1.08 Rukwa 59.2 74.1 67.4 1.25 75.2 85.5 80.9 1.14 Kigoma 70.1 68.2 69.1 0.97 97.0 79.5 87.7 0.82 Shinyanga 62.2 67.2 64.7 1.08 73.3 74.7 74.0 1.02 Kagera 73.9 77.6 75.9 1.05 96.5 93.8 95.1 0.97 Mwanza 71.2 81.8 76.5 1.15 90.4 101.0 95.7 1.12 Mara 81.1 84.7 83.0 1.04 98.5 101.6 100.2 1.03 Manyara 70.9 80.7 75.9 1.14 84.8 88.1 86.5 1.04 Njombe 86.4 91.7 89.2 1.06 97.1 101.7 99.5 1.05 Katavi 60.3 57.7 59.1 0.96 77.7 69.6 73.7 0.90 Simiyu 69.0 74.2 71.7 1.08 86.0 85.6 85.8 1.00 Geita 63.3 68.3 65.6 1.08 86.8 81.1 84.1 0.93 Kaskazini Unguja 85.7 89.2 87.3 1.04 119.5 105.9 113.2 0.89 Kusini Unguja 90.4 92.1 91.3 1.02 114.9 110.1 112.4 0.96 Mjini Magharibi 90.0 88.8 89.4 0.99 103.8 102.9 103.4 0.99 Kaskazini Pemba 76.2 71.7 73.7 0.94 92.3 84.9 88.3 0.92 Kusini Pemba 69.6 75.7 72.6 1.09 90.0 97.5 93.7 1.08 Wealth quintile Lowest 56.1 61.5 58.7 1.10 66.9 72.3 69.6 1.08 Second 64.0 76.5 70.3 1.19 79.0 88.8 83.9 1.12 Middle 77.3 80.8 79.1 1.05 94.5 93.1 93.7 0.98 Fourth 84.1 87.2 85.7 1.04 102.6 102.1 102.3 1.00 Highest 91.4 89.7 90.5 0.98 112.8 105.6 109.0 0.94 Total 72.9 78.4 75.7 1.08 89.0 91.4 90.2 1.03 (Continued…) Housing Characteristics and Household Population • 45 Table 2.14—Continued Net attendance ratio1 Gross attendance ratio2 Background characteristic Male Female Total Gender Parity Index3 Male Female Total Gender Parity Index3 SECONDARY SCHOOL Residence Urban 40.3 33.1 36.3 0.82 54.2 42.8 48.0 0.79 Rural 13.9 18.7 16.2 1.34 17.1 22.2 19.5 1.30 Region Dodoma 14.3 13.9 14.1 0.97 17.7 20.8 18.9 1.18 Arusha 25.3 30.1 27.8 1.19 31.6 38.2 35.0 1.21 Kilimanjaro 45.1 56.6 51.3 1.25 57.1 71.1 64.7 1.25 Tanga 22.4 27.9 25.2 1.24 28.3 32.4 30.4 1.14 Morogoro 22.4 23.9 23.1 1.07 30.5 26.7 28.6 0.88 Pwani 23.7 21.4 22.6 0.90 25.8 26.4 26.1 1.02 Dar es Salaam 42.8 30.7 35.8 0.72 62.3 45.6 52.6 0.73 Lindi 15.1 18.8 17.1 1.24 19.2 22.4 20.9 1.17 Mtwara 12.1 19.6 15.5 1.61 17.5 23.8 20.3 1.36 Ruvuma 19.7 23.8 21.7 1.21 24.7 27.3 26.0 1.11 Iringa 30.3 47.1 38.1 1.56 44.8 54.6 49.4 1.22 Mbeya 26.3 26.6 26.5 1.01 34.7 32.4 33.5 0.94 Singida 23.8 34.7 28.7 1.46 26.9 41.2 33.3 1.53 Tabora 11.5 12.7 12.1 1.10 13.9 15.5 14.7 1.12 Rukwa 10.7 10.7 10.7 1.00 13.3 12.0 12.7 0.90 Kigoma 17.9 12.4 15.2 0.69 21.4 17.8 19.6 0.83 Shinyanga 15.4 10.0 12.6 0.65 18.2 13.4 15.8 0.74 Kagera 15.3 23.8 18.9 1.56 18.8 25.6 21.7 1.36 Mwanza 21.2 20.0 20.6 0.94 28.7 22.1 25.3 0.77 Mara 19.1 22.1 20.9 1.16 23.3 22.9 23.0 0.98 Manyara 11.5 31.2 21.0 2.72 14.5 40.2 26.9 2.78 Njombe 15.9 31.2 22.1 1.96 24.0 39.8 30.4 1.66 Katavi 15.1 10.8 12.9 0.72 18.8 12.1 15.3 0.64 Simiyu 17.0 18.8 17.8 1.10 20.0 23.4 21.6 1.17 Geita 16.4 11.4 14.2 0.70 20.2 15.3 18.1 0.76 Kaskazini Unguja 21.5 36.8 28.7 1.71 26.0 40.8 33.0 1.57 Kusini Unguja 38.7 40.2 39.5 1.04 39.1 41.3 40.3 1.06 Mjini Magharibi 59.4 54.1 56.4 0.91 75.8 69.0 72.0 0.91 Kaskazini Pemba 32.9 33.8 33.4 1.03 39.4 33.8 36.4 0.86 Kusini Pemba 33.2 38.7 36.0 1.16 39.4 41.3 40.4 1.05 Wealth quintile Lowest 5.9 5.8 5.8 0.99 6.4 7.2 6.8 1.12 Second 8.6 10.6 9.6 1.24 10.7 12.6 11.6 1.17 Middle 15.2 19.8 17.2 1.31 18.9 22.7 20.6 1.20 Fourth 27.6 35.9 31.7 1.30 35.0 44.8 39.9 1.28 Highest 47.4 36.2 41.0 0.77 63.8 46.4 53.9 0.73 Total 21.7 23.8 22.8 1.10 28.1 29.6 28.8 1.05 1 The NAR for primary school is the percentage of the primary-school-age (age 7-13) population that is attending primary school. The NAR for secondary school is the percentage of the secondary-school-age (age 14-17) population that is attending secondary school. By definition the NAR cannot exceed 100 percent. 2 The GAR for primary school is the total number of primary school students, expressed as a percentage of the official primary-school-age population. The GAR for secondary school is the total number of secondary school students, expressed as a percentage of the official secondary- school-age population. If there are significant numbers of overage and underage students at a given level of schooling, the GAR can exceed 100 percent. 3 The Gender Parity Index for primary school is the ratio of the primary school NAR(GAR) for females to the NAR(GAR) for males. The Gender Parity Index for secondary school is the ratio of the secondary school NAR(GAR) for females to the NAR(GAR) for males. 46 • Housing Characteristics and Household Population Table 2.15 Household food security Percent distribution of household by usual number of meals per day, number of days that meat or fish was consumed during the last week, and frequency of problems satisfying food needs in the past year, according to residence, Tanzania DHS-MIS 2015-16 Mainland Zanzibar Total Food security characteristic Urban Rural Total Usual number of meals per day 1 meal 1.8 2.0 1.9 1.0 1.9 2 meals 21.0 43.0 35.7 38.8 35.8 3+ meals 77.1 55.0 62.4 60.2 62.3 Total 100.0 100.0 100.0 100.0 100.0 Number of days consumed meat or fish in the past week 0 14.6 35.3 28.5 5.6 27.9 1 16.9 20.1 19.1 5.6 18.7 2 20.1 18.2 18.8 9.0 18.6 3 17.

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